Removing the effect of SVD algorithmic artifacts present in quantitative MR perfusion studies

A Bayesian estimation method for cerebral blood flow measurement by area-detector CT perfusion imaging

PURPOSE

Bayesian estimation with advanced noise reduction (BEANR) in CT perfusion (CTP) could deliver more reliable cerebral blood flow (CBF) measurements than the commonly used reformulated singular value decomposition (rSVD). We compared the efficacy of CBF measurement by CTP using BEANR and rSVD, evaluating both relative to N-isopropyl-p-[(123) I]- iodoamphetamine (¹²³I-IMP) single-photon emission computed tomography (SPECT) as a reference standard, in patients with cerebrovascular disease.

METHODS

Thirty-one patients with suspected cerebrovascular disease underwent both CTP on a 320 detector-row CT system and SPECT. We applied rSVD and BEANR in the ischemic and contralateral regions to create CBF maps and calculate CBF ratios from the ischemic side to the healthy contralateral side (CBF index). The analysis involved comparing the CBF index between CTP methods and SPECT using Pearson's correlation and limits of agreement determined with Bland-Altman analyses, before comparing the mean difference in the CBF index between each CTP method and SPECT using the Wilcoxon matched pairs signed-rank test.

RESULTS

The CBF indices of BEANR and ¹²³I-IMP SPECT were significantly and positively correlated (r = 0.55, p < 0.0001), but there was no significant correlation between the rSVD method and SPECT (r = 0.15, p > 0.05). BEANR produced smaller limits of agreement for CBF than rSVD. The mean difference in the CBF index between BEANR and SPECT differed significantly from that between rSVD and SPECT (p < 0.001).

CONCLUSIONS

BEANR has a better potential utility for CBF measurement in CTP than rSVD compared to SPECT in patients with cerebrovascular disease.

[Novel Perfusion Evaluation Method Using Phase-ratio Image Map in Head 4D-CT]

PURPOSE

CT perfusion (CTP) is a powerful tool for the assessment of cerebrovascular disease. However, CTP maps are significantly different depending on CTP software and algorithm, even when using identical image data. We developed a phase-ratio image map (PI map), which was a novel perfusion map, without using CTP software. The purpose of this study was to investigate the usefulness of the PI map by comparing it with a positron emission tomography (PET) image.

METHODS

Twenty patients (16 men, 4 women; mean age: 61.6 years) with unilateral cervical and intracranial steno-occlusive disease underwent CTP. CTP source images were obtained at 1-s intervals of 23 times and 5 intervals using dynamic multiphase imaging. An early-phase image was generated by computing the average of CT images for 5 s in the vicinity of the peak enhancement curve of a normal hemisphere. A delayed-phase image was generated by computing the average of CT images for 5 s immediately after the early phase. The PI map was created by dividing the delayed-phase image by the early-phase image. We investigated the validity of the PI map compared with PET-cerebral blood flow (CBF). Lesion-to-normal ratios between a PET-CBF and the PI map or two conventional CTP-CBFs were observed and compared, and the relative errors were also compared.

RESULT

There was a strong correlation between the PET-CBF and the PI map (R=0.82). Correlations between the PET-CBF and two CTP-CBFs were weak (R=0.30) and middle (R=0.62), respectively. The relative error between the PI map and the PET-CBF was within 10% in most cases.

CONCLUSION

The PI map was more similar to the PET-CBF on perfusion evaluation, and did not depend on CTP software. The robustness and simplicity of the PI mapping method would be advantageous compared with conventional CTP mapping methods.

A 4D CT digital phantom of an individual human brain for perfusion analysis

Brain perfusion is of key importance to assess brain function. Modern CT scanners can acquire perfusion maps of the cerebral parenchyma in vivo at submillimeter resolution. These perfusion maps give insights into the hemodynamics of the cerebral parenchyma and are critical for example for treatment decisions in acute stroke. However, the relations between acquisition parameters, tissue attenuation curves, and perfusion values are still poorly understood and cannot be unraveled by studies involving humans because of ethical concerns. We present a 4D CT digital phantom specific for an individual human brain to analyze these relations in a bottom-up fashion. Validation of the signal and noise components was based on 1,000 phantom simulations of 20 patient imaging data. This framework was applied to quantitatively assess the relation between radiation dose and perfusion values, and to quantify the signal-to-noise ratios of penumbra regions with decreasing sizes in white and gray matter. This is the first 4D CT digital phantom that enables to address clinical questions without having to expose the patient to additional radiation dose.

Cerebrovascular reactivity and white matter integrity

OBJECTIVE

To compare the diffusion and perfusion MRI metrics of normal-appearing white matter (NAWM) with and without impaired cerebrovascular reactivity (CVR).

METHODS

Seventy-five participants with moderate to severe leukoaraiosis underwent blood oxygen level-dependent CVR mapping using a 3T MRI system with precise carbon dioxide stimulus manipulation. Several MRI metrics were statistically compared between areas of NAWM with positive and negative CVR using one-way analysis of variance with Bonferroni correction for multiple comparisons.

RESULTS

Areas of NAWM with negative CVR showed a significant reduction in fractional anisotropy by a mean (SD) of 3.7% (2.4), cerebral blood flow by 22.1% (8.2), regional cerebral blood volume by 22.2% (7.0), and a significant increase in mean diffusivity by 3.9% (3.1) and time to maximum by 10.9% (13.2) (p < 0.01), compared to areas with positive CVR.

CONCLUSIONS

Impaired CVR is associated with subtle changes in the tissue integrity of NAWM, as evaluated using several quantitative diffusion and perfusion MRI metrics. These findings suggest that impaired CVR may contribute to the progression of white matter disease.

Vascular Dysfunction in Leukoaraiosis

BACKGROUND AND PURPOSE

The pathogenesis of leukoaraiosis has long been debated. This work addresses a less well-studied mechanism, cerebrovascular reactivity, which could play a leading role in the pathogenesis of this disease. Our aim was to evaluate blood flow dysregulation and its relation to leukoaraiosis.

MATERIALS AND METHODS

Cerebrovascular reactivity, the change in the blood oxygen level-dependent 3T MR imaging signal in response to a consistently applied step change in the arterial partial pressure of carbon dioxide, was measured in white matter hyperintensities and their contralateral spatially homologous normal-appearing white matter in 75 older subjects (age range, 50-91 years; 40 men) with leukoaraiosis. Additional quantitative evaluation of regions of leukoaraiosis was performed by using diffusion (n = 75), quantitative T2 (n = 54), and DSC perfusion MRI metrics (n = 25).

RESULTS

When we compared white matter hyperintensities with contralateral normal-appearing white matter, cerebrovascular reactivity was lower by a mean of 61.2% ± 22.6%, fractional anisotropy was lower by 44.9 % ± 6.9%, and CBF was lower by 10.9% ± 11.9%. T2 was higher by 61.7% ± 13.5%, mean diffusivity was higher by 59.0% ± 11.7%, time-to-maximum was higher by 44.4% ± 30.4%, and TTP was higher by 6.8% ± 5.8% (all P < .01). Cerebral blood volume was lower in white matter hyperintensities compared with contralateral normal-appearing white matter by 10.2% ± 15.0% (P = .03).

CONCLUSIONS

Not only were resting blood flow metrics abnormal in leukoaraiosis but there is also evidence of reduced cerebrovascular reactivity in these areas. Studies have shown that reduced cerebrovascular reactivity is more sensitive than resting blood flow parameters for assessing vascular insufficiency. Future work is needed to examine the sensitivity of resting-versus-dynamic blood flow measures for investigating the pathogenesis of leukoaraiosis.

Technical Pitfalls of Signal Truncation in Perfusion MRI of Glioblastoma

Dynamic susceptibility contrast (DSC) perfusion-weighted imaging (PWI) is widely used in clinical settings for the radiological diagnosis of brain tumor. The signal change in brain tissue in gradient echo-based DSC PWI is much higher than in spin echo-based DSC PWI. Due to its exquisite sensitivity, gradient echo-based sequence is the preferred method for imaging of all tumors except those near the base of the skull. However, high sensitivity also comes with a dynamic range problem. It is not unusual for blood volume to increase in gene-mediated cytotoxic immunotherapy-treated glioblastoma patients. The increase of fractional blood volume sometimes saturates the MRI signal during first-pass contrast bolus arrival and presents signal truncation artifacts of various degrees in the tumor when a significant amount of blood exists in the image pixels. It presents a hidden challenge in PWI, as this signal floor can be either close to noise level or just above and can go no lower. This signal truncation in the signal intensity time course is a significant issue that deserves attention in DSC PWI. In this paper, we demonstrate that relative cerebral blood volume and relative cerebral blood flow (rCBF) are underestimated due to signal truncation in DSC perfusion, in glioblastoma patients. We propose the use of second-pass tissue residue function in rCBF calculation using least-absolute-deviation deconvolution to avoid the underestimation problem.

Reliability of CT perfusion-derived CBF in relation to hemodynamic compromise in patients with cerebrovascular steno-occlusive disease: a comparative study with 15O PET

In the bolus tracking technique with computed tomography (CT) or magnetic resonance imaging, cerebral blood flow (CBF) is computed from deconvolution analysis, but its accuracy is unclear. To evaluate the reliability of CT perfusion (CTP)-derived CBF, we examined 27 patients with symptomatic or asymptomatic unilateral cerebrovascular steno-occlusive disease. Results from three deconvolution algorithms, standard singular value decomposition (sSVD), delay-corrected SVD (dSVD), and block-circulant SVD (cSVD), were compared with (15)O positron emission tomography (PET) as a reference standard. To investigate CBF errors associated with the deconvolution analysis, differences in lesion-to-normal CBF ratios between PET and CTP were correlated with prolongation of arterial-tissue delay (ATD) and mean transit time (MTT) in the lesion hemisphere. Computed tomography perfusion results strongly depended on the deconvolution algorithms used. Standard singular value decomposition showed ATD-dependent underestimation of CBF ratio, whereas cSVD showed overestimation of the CBF ratio when MTT was severely prolonged in the lesions. The computer simulations reproduced the trend observed in patients. Deconvolution by dSVD can provide lesion-to-normal CBF ratios less dependent on ATD and MTT, but requires accurate ATD maps in advance. A practical and accurate method for CTP is required to assess CBF in patients with MTT-prolonged regions.

Cerebrovascular MRI: a review of state-of-the-art approaches, methods and techniques

Cerebrovascular imaging is of great interest in the understanding of neurological disease. MRI is a non-invasive technology that can visualize and provide information on: (i) the structure of major blood vessels; (ii) the blood flow velocity in these vessels; and (iii) the microcirculation, including the assessment of brain perfusion. Although other medical imaging modalities can also interrogate the cerebrovascular system, MR provides a comprehensive assessment, as it can acquire many different structural and functional image contrasts whilst maintaining a high level of patient comfort and acceptance. The extent of examination is limited only by the practicalities of patient tolerance or clinical scheduling limitations. Currently, MRI methods can provide a range of metrics related to the cerebral vasculature, including: (i) major vessel anatomy via time-of-flight and contrast-enhanced imaging; (ii) blood flow velocity via phase contrast imaging; (iii) major vessel anatomy and tissue perfusion via arterial spin labeling and dynamic bolus passage approaches; and (iv) venography via susceptibility-based imaging. When designing an MRI protocol for patients with suspected cerebral vascular abnormalities, it is appropriate to have a complete understanding of when to use each of the available techniques in the 'MR angiography toolkit'. In this review article, we: (i) overview the relevant anatomy, common pathologies and alternative imaging modalities; (ii) describe the physical principles and implementations of the above listed methods; (iii) provide guidance on the selection of acquisition parameters; and (iv) describe the existing and potential applications of MRI to the cerebral vasculature and diseases. The focus of this review is on obtaining an understanding through the application of advanced MRI methodology of both normal and abnormal blood flow in the cerebrovascular arteries, capillaries and veins.

Comparison of CT perfusion summary maps to early diffusion-weighted images in suspected acute middle cerebral artery stroke

OBJECTIVES

To assess the accuracy and reliability of one vendor's (Vital Images, Toshiba Medical, Minnetonka, MN) automated CT perfusion (CTP) summary maps in identification and volume estimation of infarcted tissue in patients with acute middle cerebral artery (MCA) distribution infarcts.

SUBJECTS AND METHODS

From 1085 CTP examinations over 5.5 years, 43 diffusion-weighted imaging (DWI)-positive patients were included who underwent both CTP and DWI <12 h after symptom onset, with another 43 age-matched patients as controls (DWI-negative). Automated delay-corrected postprocessing software (DC-SVD) generated both infarct "core only" and "core+penumbra" CTP summary maps. Three reviewers independently tabulated Alberta Stroke Program Early CT scores (ASPECTS) of both CTP summary maps and coregistered DWI.

RESULTS

Of 86 included patients, 36 had DWI infarct volumes ≤70 ml, 7 had volumes >70 ml, and 43 were negative; the automated CTP "core only" map correctly classified each as >70 ml or ≤70 ml, while the "core+penumbra" map misclassified 4 as >70 ml. There were strong correlations between DWI volume with both summary map-based volumes: "core only" (r=0.93), and "core+penumbra" (r=0.77) (both p<0.0001). Agreement between ASPECTS scores of infarct core on DWI with summary maps was 0.65-0.74 for "core only" map, and 0.61-0.65 for "core+penumbra" (both p<0.0001). Using DWI-based ASPECTS scores as the standard, the accuracy of the CTP-based maps were 79.1-86.0% for the "core only" map, and 83.7-88.4% for "core+penumbra."

CONCLUSION

Automated CTP summary maps appear to be relatively accurate in both the detection of acute MCA distribution infarcts, and the discrimination of volumes using a 70 ml threshold.

Modeling and correction of bolus dispersion effects in dynamic susceptibility contrast MRI

PURPOSE

Bolus dispersion in DSC-MRI can lead to errors in cerebral blood flow (CBF) estimation by up to 70% when using singular value decomposition analysis. However, it might be possible to correct for dispersion using two alternative methods: the vascular model (VM) and control point interpolation (CPI). Additionally, these approaches potentially provide a means to quantify the microvascular residue function.

METHODS

VM and CPI were extended to correct for dispersion by means of a vascular transport function. Simulations were performed at multiple dispersion levels and an in vivo analysis was performed on a healthy subject and two patients with carotid atherosclerotic disease.

RESULTS

Simulations showed that methods that could not address dispersion tended to underestimate CBF (ratio in CBF estimation, CBFratio = 0.57-0.77) in the presence of dispersion; whereas modified CPI showed the best performance at low-to-medium dispersion; CBFratio = 0.99 and 0.81, respectively. The in vivo data showed trends in CBF estimation and residue function that were consistent with the predictions from simulations.

CONCLUSION

In patients with atherosclerotic disease the estimated residue function showed considerable differences in the ipsilateral hemisphere. These differences could partly be attributed to dispersive effects arising from the stenosis when dispersion corrected CPI was used. It is thus beneficial to correct for dispersion in perfusion analysis using this method.

Arterial input function in perfusion MRI: a comprehensive review

Cerebral perfusion, also referred to as cerebral blood flow (CBF), is one of the most important parameters related to brain physiology and function. The technique of dynamic-susceptibility contrast (DSC) MRI is currently the most commonly used MRI method to measure perfusion. It relies on the intravenous injection of a contrast agent and the rapid measurement of the transient signal changes during the passage of the bolus through the brain. Central to quantification of CBF using this technique is the so-called arterial input function (AIF), which describes the contrast agent input to the tissue of interest. Due to its fundamental role, there has been a lot of progress in recent years regarding how and where to measure the AIF, how it influences DSC-MRI quantification, what artefacts one should avoid, and the design of automatic methods to measure the AIF. The AIF is also directly linked to most of the major sources of artefacts in CBF quantification, including partial volume effect, bolus delay and dispersion, peak truncation effects, contrast agent non-linearity, etc. While there have been a number of good review articles on DSC-MRI over the years, these are often comprehensive but, by necessity, with limited in-depth discussion of the various topics covered. This review article covers in greater depth the issues associated with the AIF and their implications for perfusion quantification using DSC-MRI.

The 39 steps: evading error and deciphering the secrets for accurate dynamic susceptibility contrast MRI

Dynamic susceptibility contrast (DSC) MRI is the most commonly used MRI method to assess cerebral perfusion and other related haemodynamic parameters. Although the technique is well established and used routinely in clinical centres, there are still many problems that impede accurate perfusion quantification. In this review article, we present 39 steps which guide the reader through the theoretical principles, practical decisions, potential problems, current limitations and latest advances in DSC-MRI. The 39 steps span the collection, analysis and interpretation of DSC-MRI data, expounding issues and possibilities relating to the contrast agent, the acquisition of DSC-MRI data, data pre-processing, the contrast concentration-time course, the arterial input function, deconvolution, common perfusion parameters, post-processing possibilities, patient studies, absolute versus relative quantification and automated analysis methods.

Optimisation of vascular input and output functions in CT-perfusion imaging using 256(or more)-slice multidetector CT

OBJECTIVES

To evaluate the accuracy and reproducibility of CT-perfusion (CTP) by finding the optimal artery for the arterial input function (AIF) and re-evaluating the necessity of the venous output function (VOF).

METHODS

Forty-four acute ischaemic stroke patients who underwent non-enhanced CT, CTP and CT-angiography using 256-slice multidetector computed tomography (MDCT) were evaluated. The anterior cerebral artery (ACA), middle cerebral artery (MCA), internal carotid artery (ICA) and basilar artery were selected as the AIF. Subsequently the resulting area under the time-enhancement curve of the AIF (AUCAIF) and quantitative perfusion measurements were analysed by repeated measures ANOVA and subsequently the paired t test. To evaluate reproducibility we examined if the VOF could be deleted by comparing the perfusion measurements using versus not using the VOF (paired t test).

RESULTS

The AUCAIF and perfusion measurements resulting from the different AIFs showed significant group differences (all P < 0.0001). The ICA had the largest AUCAIF and resulted in the highest mean transient time (MTT) and lowest cerebral blood flow (CBF), whereas the basilar artery showed the lowest cerebral blood volume (CBV). Not using the VOF showed significantly higher CBV and CBF in 66 % of patients on the ipsilateral (P < 0.0001 and P = 0.007, respectively) and contralateral hemisphere (P < 0.0001 and P = 0.019, respectively).

CONCLUSION

Selecting the ICA as the AIF and continuing the use of the VOF would improve the accuracy of CTP.

KEY POINTS

• Perfusion imaging is an increasingly important aspect of multidetector computed tomography (MDCT). • Vascular input functions were evaluated for CT-perfusion using 256-slice MDCT. • Selecting different arterial input functions (AIFs) leads to variation in quantitative values. • Using the internal carotid artery for AIF provides optimal perfusion values. • Deleting the venous output function would be detrimental for validity.

Correction for arterial-tissue delay and dispersion in absolute quantitative cerebral perfusion DSC MR imaging

The singular value decomposition deconvolution of cerebral tissue concentration-time curves with the arterial input function is commonly used in dynamic susceptibility contrast cerebral perfusion MR imaging. However, it is sensitive to the time discrepancy between the arrival of the bolus in the tissue concentration-time curve and the arterial input function signal. This normally causes inaccuracy in the quantitative perfusion maps due to delay and dispersion effects. A comprehensive correction algorithm has been achieved through slice-dependent time-shifting of the arterial input function, and a delay-dependent dispersion correction model. The correction algorithm was tested in 11 healthy subjects and three ischemic stroke patients scanned with a quantitative perfusion pulse sequence at 1.5 T. A validation study was performed on five patients with confirmed cerebrovascular occlusive disease scanned with MRI and positron emission tomography at 3.0 T. A significant effect (P < 0.05) was reported on the quantitative cerebral blood flow and mean transit time measurements (up to 50%). There was no statistically significant effect on the quantitative cerebral blood volume values. The in vivo results were in agreement with the simulation results, as well as previous literature. This minimizes the bias in patient diagnosis due to the existing errors and artifacts in dynamic susceptibility contrast imaging.

Deconvolution with simple extrapolation for improved cerebral blood flow measurement in dynamic susceptibility contrast magnetic resonance imaging during acute ischemic stroke

Magnetic resonance (MR) perfusion imaging is a clinical technique for measuring brain blood flow parameters during stroke and other ischemic events. Ischemia in brain tissue can be difficult to accurately measure or visualize when using MR-derived cerebral blood flow (CBF) maps. The deconvolution techniques used to estimate flow can introduce a mean transit time-dependent bias following application of noise stabilization techniques. The underestimation of the CBF values, greatest in normal tissues, causes a decrease in the image contrast observed in CBF maps between normally perfused and ischemic tissues; resulting in ischemic areas becoming less conspicuous. Through application of the proposed simple extrapolation technique, CBF biases are reduced when missing high-frequency signal components in the MR data removed during deconvolution noise stabilization are restored. The extrapolation approach was compared with other methods and showed a statistically significant increase in image contrast in CBF maps between normal and ischemic tissues for white matter (P<.05) and performed better than most other methods for gray matter. Receiver operator characteristic curve analysis demonstrated that extrapolated CBF maps better-detected penumbral regions. Extrapolated CBF maps provided more accurate CBF estimates in simulations, suggesting that the approach may provide a better prediction of outcome in the absence of treatment.

Arterial input function placement for accurate CT perfusion map construction in acute stroke

OBJECTIVE

The objective of our study was to evaluate the effect of varying arterial input function (AIF) placement on the qualitative and quantitative CT perfusion parameters.

MATERIALS AND METHODS

Retrospective analysis of CT perfusion data was performed on 14 acute stroke patients with a proximal middle cerebral artery (MCA) clot. Cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) maps were constructed using a systematic method by varying only the AIF placement in four positions relative to the MCA clot including proximal and distal to the clot in the ipsilateral and contralateral hemispheres. Two postprocessing software programs were used to evaluate the effect of AIF placement on perfusion parameters using a delay-insensitive deconvolution method compared with a standard deconvolution method.

RESULTS

One hundred sixty-eight CT perfusion maps were constructed for each software package. Both software programs generated a mean CBF at the infarct core of < 12 mL/100 g/min and a mean CBV of < 2 mL/100 g for AIF placement proximal to the clot in the ipsilateral hemisphere and proximal and distal to the clot in the contralateral hemisphere. For AIF placement distal to the clot in the ipsilateral hemisphere, the mean CBF significantly increased to 17.3 mL/100 g/min with delay-insensitive software and to 19.4 mL/100 g/min with standard software (p < 0.05). The mean MTT was significantly decreased for this AIF position. Furthermore, this AIF position yielded qualitatively different parametric maps, being most pronounced with MTT and CBF. Overall, CBV was least affected by AIF location.

CONCLUSION

For postprocessing of accurate quantitative CT perfusion maps, laterality of the AIF location is less important than avoiding AIF placement distal to the clot as detected on CT angiography. This pitfall is less severe with deconvolution-based software programs using a delay-insensitive technique than with those using a standard deconvolution method.

Diffusion and perfusion MR imaging of acute ischemic stroke

Diffusion and perfusion MR imaging have proven to be highly useful in the clinical description and understanding of acute and hyperacute ischemic stroke. In this article, the authors give a brief overview of the basic concepts of diffusion and perfusion imaging and describe some of the current developments, applications, challenges, and limitations of these techniques as applied to cerebral ischemia.

Improved residue function and reduced flow dependence in MR perfusion using least-absolute-deviation regularization

Cerebral blood flow (CBF) estimates derived from singular value decomposition (SVD) of time intensity curves from Gadolinium bolus perfusion-weighted imaging are known to underestimate CBF, especially at high flow rates. We report the development of a model-independent delay-invariant deconvolution technique using least-absolute-deviation (LAD) regularization to improve the CBF estimation accuracy. Computer simulations were performed to compare the accuracy of CBF estimates derived from LAD, reformulated SVD (rSVD) and standard SVD (sSVD) techniques. Simulations were performed at image signal-to-noise ratios ranging from 20 to 400, cerebral blood volumes from 1% to 10%, and CBF from 2.5 mL/100 g/min to 176.5 mL/100 g/min to estimate the effect of these parameters on the accuracy of CBF estimation. The LAD method improved the CBF estimation accuracy by up to 32% in gray matter and 23% in white matter compared with rSVD and sSVD methods. LAD method also reduces the systematic bias of rSVD and sSVD methods to baseline SNR while producing more accurate and reproducible residue function calculation than either rSVD or sSVD method. Initial clinical implementation of the method on six representative clinical cases confirm the advantages of the LAD method over rSVD and sSVD methods.

Nonlinear DeltaR*2 effects in perfusion quantification using bolus-tracking MRI

Dynamic susceptibility contrast MRI involves injection of a contrast agent, whose concentration is estimated from DeltaR*2 changes. However, measurement of contrast-agent concentration is prone to various sources of error; in particular, the commonly assumed linear relationship between contrast agent concentration and DeltaR*2 in arterial blood is known to be invalid. In this study, we characterized the associated perfusion errors. Large errors were found when the linear assumption is used; these errors were highly dependent on the choice of tissue relaxivity. The errors were greatly reduced when using the quadratic model, and were further reduced when quantifying perfusion as a relative measure. This study suggests the linear assumption should be abandoned in favor of the quadratic model. Thus, the errors are minimized leading to improved quantification that will enable perfusion MRI to continue to play an important role in quantifying perfusion in brain diseases (e.g., acute stroke).

Tracer delay-insensitive algorithm can improve reliability of CT perfusion imaging for cerebrovascular steno-occlusive disease: comparison with quantitative single-photon emission CT

BACKGROUND AND PURPOSE

Reliability of CT perfusion (CTP) algorithms has not been fully validated. We investigated whether the cerebral blood flow (CBF) values obtained by using a dynamic CTP technique with a tracer delay-insensitive deconvolution algorithm are more accurate than those obtained by using CTP with delay-sensitive algorithms in unilateral cerebrovascular steno-occlusive disease, when compared with those generated by quantitative single-photon emission CT (SPECT).

MATERIALS AND METHODS

Using CTP and iodine-123-N-isopropyl-p-iodoamphetamine SPECT with an autoradiographic quantification technique, we examined 20 patients with suggested hemodynamic ischemia due to stenosis or occlusion of the unilateral internal carotid or middle cerebral artery. The algorithms used for CTP included delay-insensitive block-circulant singular value decomposition (SVD) (bSVD) and delay-sensitive standard SVD (sSVD) and box-modulation transfer function (bMTF).

RESULTS

Absolute CBF values obtained by using CTP with bSVD were significantly lower than those obtained with SPECT, but the ratios to the nonaffected side were significantly correlated to the quantitative SPECT values with significant agreements, particularly when the arterial input function was obtained from the unaffected side. Contrastingly, CBF ratios with sSVD and bMTF were significantly underestimated, and no significant agreement was determined between CTP with sSVD or bMTF and SPECT, though there were substantial correlations between them in some parameters.

CONCLUSIONS

With the CTP technique, the insensitivity of the deconvolution algorithm to the tracer-delay effect appears to be essential for estimating semiquantitative CBF values in patients with unilateral steno-occlusive lesions.

Absolute quantification of cerebral blood flow in normal volunteers: correlation between Xe-133 SPECT and dynamic susceptibility contrast MRI

PURPOSE

To compare absolute cerebral blood flow (CBF) estimates obtained by dynamic susceptibility contrast MRI (DSC-MRI) and Xe-133 SPECT.

MATERIALS AND METHODS

CBF was measured in 20 healthy volunteers using DSC-MRI at 3T and Xe-133 SPECT. DSC-MRI was accomplished by gradient-echo EPI and CBF was calculated using a time-shift-insensitive deconvolution algorithm and regional arterial input functions (AIFs). To improve the reproducibility of AIF registration the time integral was rescaled by use of a venous output function. In the Xe-133 SPECT experiment, Xe-133 gas was inhaled over 8 minutes and CBF was calculated using a biexponential analysis.

RESULTS

The average whole-brain CBF estimates obtained by DSC-MRI and Xe-133 SPECT were 85 +/- 23 mL/(min 100 g) and 40 +/- 8 mL/(min 100 g), respectively (mean +/- SD, n = 20). The linear CBF relationship between the two modalities showed a correlation coefficient of r = 0.76 and was described by the equation CBF(MRI) = 2.4 . CBF(Xe)-7.9 (CBF in units of mL/(min 100 g)).

CONCLUSION

A reasonable positive linear correlation between MRI-based and SPECT-based CBF estimates was observed after AIF time-integral correction. The use of DSC-MRI typically results in overestimated absolute perfusion estimates and the present study indicates that this trend is further enhanced by the use of high magnetic field strength (3T).

Partial volume effect in quantitative magnetic resonance perfusion imaging

In dynamic-susceptibility contrast (DSC) magnetic resonance (MR) perfusion imaging, the cerebral blood flow (CBF) is estimated from the tissue residue function obtained through deconvolution of the contrast concentration functions. However, the reliability of CBF estimates obtained by deconvolution is sensitive to various distortions. Among the most prominent experimental limitations is the image spatial resolution, leading to partial volume effect (PVE), which arises when the size of the voxel exceeds the volume containing the arterial input signal. PVE results in distortion of the arterial input function (AIF), and directly leads to miscalculation of the CBF. This work demonstrates the degree of the CBF estimation bias that could develop as a result of PVE.

PerfTool: a software platform for investigating bolus-tracking perfusion imaging quantification strategies

PURPOSE

To develop a software platform, PerfTool (for perfusion tool), for the comprehensive evaluation of bolus-tracking quantitative perfusion imaging methods and algorithms, along with a method to rapidly visualize and evaluate the performance of algorithms.

MATERIALS AND METHODS

Algorithms were evaluated interactively with PerfTool using synthetic DeltaR2* data sets with different perfusion parameter permutations (known as test patterns). Patient data and test patterns were used to evaluate a standard singular value deconvolution (SVD) approach (sSVD) and a reformulated implementation (rSVD) that is insensitive to arterial-tissue delay (ATD), and to explore the effect of the SVD regularization parameter (p(SVD)) on CBF estimates.

RESULTS

The CBF overestimation resulting from sensitivity to ATD in sSVD compared to rSVD was demonstrated with the patient data, and the effect was confirmed using a test pattern. The same test pattern demonstrated the CBF underestimation resulting from high p(SVD) thresholds.

CONCLUSION

PerfTool is an extensible software tool that allows perfusion measurements to be obtained by different methods, and is flexible enough to incorporate new developments and apply them to real patient data and test patterns.

Reexamining the quantification of perfusion MRI data in the presence of bolus dispersion

PURPOSE

To determine the true impact of dispersion upon cerebral blood flow (CBF) quantification by removing an algorithm implementation-induced systematic error.

MATERIALS AND METHODS

The impact of dispersion on the arterial input function (AIF) between measurement and entry into the tissue of interest on CBF estimates was simulated assuming: 1) contralateral circulation flow that introduces a true arterial tissue delay (ATD)-related dispersive component; and 2) the presence of an arterial stenosis that disperses and shifts the AIF peak entering the tissue; increasing the apparent ATD relative to the original AIF.

RESULTS

Previously reported CBF estimates for the stenosis dispersion model were found to be a mixture of true dispersive effects and an algorithm implementation-induced systematic error. The true CBF(MEASURED)/CBF(NO-DISPERSION) ratios for short mean transit times (MTT) (normal) and long MTT (infarcted) tissue were similar for both dispersion models evaluated; this was an unanticipated result. The CBF quantification inaccuracies induced through the dispersion model truly related to ATD were lower than for the local stenosis-based dispersion for small ATD values.

CONCLUSION

Correcting the systematic error present in a previous deconvolution study removes the reported ATD-related impact on CBF quantification. The impact of dispersion was smaller than half that reported in previous simulation studies.

Improved dynamic susceptibility contrast (DSC)-MR perfusion estimates by motion correction

PURPOSE

To investigate the effect of patient motion on quantitative cerebral blood flow (CBF) maps in ischemic stroke patients and to evaluate the efficacy of a motion-correction scheme.

MATERIALS AND METHODS

Perfusion data from 25 ischemic stroke patients were selected for analysis. Two motion profiles were applied to a digital anthropomorphic brain phantom to estimate accuracy. CBF images were generated for motion-corrupted and motion-corrected data. To correct for motion, rigid-body registration was performed. The realignment parameters and mean CBF in regions of interest were recorded.

RESULTS

All patient data with motion exhibited visibly reduced intervolume misalignment after motion correction. Improved flow delineation between different tissues and a more clearly defined ischemic lesion (IL) were achieved in the motion-corrected CBF. A significant difference occurred in the IL (P < 0.05) for patients with severe motion with an average difference between corrupted and corrected data of 4.8 mL/minute/100 g. The phantom data supported the patient results with better CBF accuracy after motion correction and high registration accuracy (<1 mm translational and <1 degrees rotational error).

CONCLUSION

Motion degrades flow differentiation between adjacent tissues in CBF maps and can cause ischemic severity to be underestimated. A registration motion correction scheme improves dynamic susceptibility contrast (DSC)-MR perfusion estimates.

Pixel-by-pixel deconvolution of bolus-tracking data: optimization and implementation

Quantification of haemodynamic parameters with a deconvolution analysis of bolus-tracking data is an ill-posed problem which requires regularization. In a previous study, simulated data without structural errors were used to validate two methods for a pixel-by-pixel analysis: standard-form Tikhonov regularization with either the L-curve criterion (LCC) or generalized cross validation (GCV) for selecting the regularization parameter. However, problems of image artefacts were reported when the methods were applied to patient data. The aim of this study was to investigate the nature of these problems in more detail and evaluate strategies of optimization for routine application in the clinic. In addition we investigated to which extent the calculation time of the algorithm can be minimized. In order to ensure that the conclusions are relevant for a larger range of clinical applications, we relied on patient data for evaluation of the algorithms. Simulated data were used to validate the conclusions in a more quantitative manner. We conclude that the reported problems with image quality can be removed by appropriate optimization of either LCC or GCV. In all examples this could be achieved with LCC without significant perturbation of the values in pixels where the regularization parameter was originally selected accurately. GCV could not be optimized for the renal data, and in the CT data only at the cost of image resolution. Using the implementations given, calculation times were sufficiently short for routine application in the clinic.

Improved deconvolution of perfusion MRI data in the presence of bolus delay and dispersion

Cerebral blood flow (CBF) is commonly estimated from the maximum of the residue function deconvolved from bolus-tracking data. The bolus may become delayed and/or dispersed in the vessels feeding the tissue, resulting in the calculation of an effective residue function, Reff(t), whose shape reflects the distortion of the bolus as well as the hemodynamic tissue status. Consequently the CBF is often underestimated. Since regularizing the deconvolution introduces additional distortions to Reff(t), it is impossible to distinguish a true decrease in the CBF from bias introduced by abnormal vasculature. This may result in misidentification of tissue regions at risk of infarction, which could have serious clinical consequences. We propose a modified maximum-likelihood expectation-maximization (mML-EM) method, which is shown by way of simulations to improve the characterization of Reff(t) across a wide range of shapes. A pointwise termination approach for the iteration minimizes the effects of noise, and appropriate integral approximations minimize discretization errors. mML-EM was applied to data from a patient with left internal carotid artery (ICA) occlusion. The shape of each calculated Reff(t) was used to create a map indicating voxels affected by bolus delay and/or dispersion, where CBF estimates are inherently unreliable. Such maps would be a useful adjunct for interpreting bolus-tracking data.

Stroke Imaging at 3.0 T

Stroke is a devastating disease with a complex pathophysiology. It is a major cause of death and disability in North America. To fully characterize its extent and effects, one requires numerous specialized anatomical and functional MR techniques, specifically diffusion-weighted imaging, MR angiography, and perfusion-weighted imaging. The advent of 3.0 T clinical scanners has the potential to provide higher quality information in potentially less time compared with 1.5 T stroke-specific MR imaging protocols. This article gives a brief overview of stroke, presents the principles and clinical applications of the relevant MR techniques required for diagnostic stroke imaging at high field, and discusses the advantages, challenges, and limitations of 3.0 T imaging as they relate to stroke.