Ronnie Wirestam

Lund University, Lund, Skåne, Sweden

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Publications (98)196.3 Total impact

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    ABSTRACT: Most approaches to arterial spin labelling (ASL) data analysis aim to provide a quantitative measure of the cerebral blood flow (CBF). This study, however, focuses on the measurement of the transfer time of blood water through the capillaries to the parenchyma (referred to as the capillary transfer time, CTT) as an alternative parameter to characterise the haemodynamics of the system. The method employed is based on a non-compartmental model, and no measurements need to be added to a common time-resolved ASL experiment. Brownian motion of labelled spins in a potential was described by a one-dimensional general Langevin equation as the starting point, and as a Fokker-Planck differential equation for the averaged distribution of labelled spins at the end point, which takes into account the effects of flow and dispersion of labelled water by the pseudorandom nature of the microvasculature and the transcapillary permeability. Multi-inversion time (multi-TI) ASL data were acquired in 14 healthy subjects on two occasions in a test-retest design, using a pulsed ASL sequence and three-dimensional gradient and spin echo (3D-GRASE) readout. Based on an error analysis to predict the size of a region of interest (ROI) required to obtain reasonably precise parameter estimates, data were analysed in two relatively large ROIs, i.e. the occipital lobe (OC) and the insular cortex (IC). The average values of CTT in OC were 260 ± 60 ms in the first experiment and 270 ± 60 ms in the second experiment. The corresponding IC values were 460 ± 130 ms and 420 ± 139 ms, respectively. Information related to the water transfer time may be important for diagnostics and follow-up of cerebral conditions or diseases characterised by a disrupted blood-brain barrier or disturbed capillary blood flow. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
    NMR in Biomedicine 07/2015; 28(8). DOI:10.1002/nbm.3344 · 3.04 Impact Factor
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    ABSTRACT: To evaluate and mutually compare the tail-scaling approach and the prebolus administration concept for reduction of arterial partial volume effects (PVEs), because reproducible absolute quantification of cerebral blood flow (CBF) by dynamic susceptibility contrast magnetic resonance imaging (MRI) is often hampered by PVEs in the arterial input function (AIF) registration. Twenty healthy volunteers were scanned in a test-retest study with 7-20 days between investigations to examine the quantitative values and the repeatability of CBF estimates obtained from the tail-scaling and the prebolus administration approaches. Average grey matter CBF was 80 ± 18 mL/100 g/min (mean ± SD) using tail-scaling and 56 ± 18 mL/100 g/min using prebolus administration. The intraclass correlation coefficient was 0.52 for the tail-scaling approach and 0.86 for the prebolus administration concept. Both correction methods resulted in considerably reduced arterial PVEs, leading to quantitative estimates of perfusion approaching those typically obtained by other perfusion modalities. The CBF estimates obtained using the prebolus administration concept showed superior repeatability. Potential sources of uncertainty in the tail-scaling approach include the use of venous concentration curves influenced by PVEs or by geometric distortions (ie, vessel pixel shifts) in the steady-state period. J. Magn. Reson. Imaging 2014. © 2014 Wiley Periodicals, Inc.
    Journal of Magnetic Resonance Imaging 04/2015; 41(4). DOI:10.1002/jmri.24621 · 3.21 Impact Factor
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    ABSTRACT: Purpose: The purpose of this study was to investigate, using simulations, a method for improved contrast agent (CA) quantification in DCE-MRI. Methods: We developed a maximum likelihood estimator that combines the phase signal in the DCE-MRI image series with an additional CA estimate, e.g. the estimate obtained from magnitude data. A number of simulations were performed to investigate the ability of the estimator to reduce bias and noise in CA estimates. Noise levels ranging from that of a body coil to that of a dedicated head coil were investigated at both 1.5T and 3T. Results: Using the proposed method, the root mean squared error in the bolus peak was reduced from 2.24 to 0.11 mM in the vessels and 0.16 to 0.08 mM in the tumor rim for a noise level equivalent of a 12-channel head coil at 3T. No improvements were seen for tissues with small CA uptake, such as white matter. Conclusion: Phase information reduces errors in the estimated CA concentrations. A larger phase response from higher field strengths or higher CA concentrations yielded better results. Issues such as background phase drift need to be addressed before this method can be applied in vivo. Magn Reson Med 74:1156-1164, 2015. © 2014 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 10/2014; 74(4). DOI:10.1002/mrm.25490 · 3.57 Impact Factor
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    ABSTRACT: Arterial partial-volume effects (PVEs) often hamper reproducible absolute quantification of cerebral blood flow (CBF) and cerebral blood volume (CBV) obtained by dynamic susceptibility contrast MRI (DSC-MRI). The aim of this study was to examine whether arterial PVEs in DSC-MRI data can be minimized by rescaling the arterial input function (AIF) using a sagittal-sinus venous output function obtained following a prebolus administration of a low dose of contrast agent. The study was carried out as a test-retest experiment in 20 healthy volunteers to examine the repeatability of the CBF and CBV estimates. All subjects were scanned twice with 7-20 days between investigations. DSC-MRI returned an overestimated average whole-brain CBF of 220 ± 44 mL/100 g/min (mean ± SD) before correction and 44 ± 15 mL/100 g/min when applying the prebolus design, averaged over all scans. Average whole-brain CBV was 20 ± 2.0 mL/100 g before correction and 4.0 ± 1.0 mL/100 g after prebolus correction. Quantitative estimates of CBF and CBV, obtained with the proposed prebolus DSC-MRI technique, approached those typically obtained by other perfusion modalities. The CBF and CBV estimates showed good repeatability. Magn Reson Med, 2013. © 2013 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 10/2014; 72(4). DOI:10.1002/mrm.25006 · 3.57 Impact Factor
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    ABSTRACT: Quantitative perfusion MRI based on arterial spin labeling (ASL) is hampered by partial volume effects (PVEs), arising due to voxel signal cross-contamination between different compartments. To address this issue, several partial volume correction (PVC) methods have been presented. Most previous methods rely on segmentation of a high-resolution T1-weighted morphological image volume that is coregistered to the low-resolution ASL data, making the result sensitive to errors in the segmentation and coregistration. In this work, we present a methodology for partial volume estimation and correction, using only low-resolution ASL data acquired with the QUASAR sequence. The methodology consists of a T1-based segmentation method, with no spatial priors, and a modified PVC method based on linear regression. The presented approach thus avoids prior assumptions about the spatial distribution of brain compartments, while also avoiding coregistration between different image volumes. Simulations based on a digital phantom as well as in vivo measurements in 10 volunteers were used to assess the performance of the proposed segmentation approach. The simulation results indicated that QUASAR data can be used for robust partial volume estimation, and this was confirmed by the in vivo experiments. The proposed PVC method yielded probable perfusion maps, comparable to a reference method based on segmentation of a high-resolution morphological scan. Corrected gray matter (GM) perfusion was 47% higher than uncorrected values, suggesting a significant amount of PVEs in the data. Whereas the reference method failed to completely eliminate the dependence of perfusion estimates on the volume fraction, the novel approach produced GM perfusion values independent of GM volume fraction. The intra-subject coefficient of variation of corrected perfusion values was lowest for the proposed PVC method. As shown in this work, low-resolution partial volume estimation in connection with ASL perfusion estimation is feasible, and provides a promising tool for decoupling perfusion and tissue volume. Copyright © 2014 John Wiley & Sons, Ltd.
    NMR in Biomedicine 09/2014; 27(9). DOI:10.1002/nbm.3164 · 3.04 Impact Factor
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    ABSTRACT: Background Due to limited SNR the cerebral applications of the intravoxel incoherent motion (IVIM) concept have been sparse. MRI hardware developments have resulted in improved SNR and this may justify a reassessment of IVIM imaging for non-invasive quantification of the cerebral blood volume (CBV) as a first step towards determining the optimal field strength. Purpose To investigate intravoxel incoherent motion imaging for its potential to assess cerebral blood volume (CBV) at three different MRI field strengths. Materials and Methods Four volunteers were scanned twice at 1.5 T, 3 T as well as 7 T. By correcting for field-strength-dependent effects of relaxation, estimates of corrected CBV (cCBV) were obtained in deep grey matter (DGM), frontal grey matter (FGM) and frontal white matter (FWM), using Bayesian analysis. In addition, simulations were performed to facilitate the interpretation of experimental data. Results In DGM, FGM and FWM we obtained cCBV estimates of 2.2 ml/100 ml, 2.7 ml/100 ml, 1.4 ml/100 ml at 1.5 T; 3.7 ml/100 ml, 5.0 ml/100 ml, 3.2 ml/100 ml at 3 T and 15.5 ml/100 ml, 20.3 ml/100 ml, 7.0 ml/100 ml at 7 T. Conclusion Quantitative cCBV values obtained at 1.5 T and 3 T corresponded better to physiological reference values, while 7 T showed the largest deviation from expected values. Simulations of synthetic tissue voxels indicated that the discrepancy at 7 T can partly be explained by SNR issues. Results were generally more repeatable at 7 T (intraclass correlation coefficient, ICC = 0.84) than at 1.5 T (ICC = 0.68) and 3 T (ICC = 0.46).
    Magnetic Resonance Imaging 08/2014; 32(10). DOI:10.1016/j.mri.2014.07.013 · 2.09 Impact Factor
  • André Ahlgren · Ronnie Wirestam · Freddy Ståhlberg · Linda Knutsson ·

    ISMRM 2014, Milano; 04/2014
  • André Ahlgren · Ronnie Wirestam · Freddy Ståhlberg · Linda Knutsson ·
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    ABSTRACT: The aim of this study was to demonstrate a new automatic brain segmentation method in magnetic resonance imaging (MRI). The signal of a spoiled gradient-recalled echo (SPGR) sequence acquired with multiple flip angles was used to map T1, and a subsequent fit of a multi-compartment model yielded parametric maps of partial volume estimates of the different compartments. The performance of the proposed method was assessed through simulations as well as in-vivo experiments in five healthy volunteers. Simulations indicated that the proposed method was capable of producing robust segmentation maps with good reliability. Mean bias was below 3 % for all tissue types, and the corresponding similarity index (Dice's coefficient) was over 95 % (SNR = 100). In-vivo experiments yielded realistic segmentation maps, with comparable quality to results obtained with an established segmentation method. Relative whole-brain cerebrospinal fluid, grey matter, and white matter volumes were (mean ± SE) respectively 6.8 ± 0.5, 47.3 ± 1.1, and 45.9 ± 1.3 % for the proposed method, and 7.5 ± 0.6, 46.2 ± 1.2, and 46.3 ± 0.9 % for the reference method. The proposed approach is promising for brain segmentation and partial volume estimation. The straightforward implementation of the method is attractive, and protocols that already rely on SPGR-based T1 mapping may employ this method without additional scans.
    MAGMA Magnetic Resonance Materials in Physics Biology and Medicine 03/2014; 27(6):551-565. DOI:10.1007/s10334-014-0439-2 · 2.87 Impact Factor
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    ABSTRACT: 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. 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). For segmented grey matter (GM) regions of interests (ROIs), pCASL-based CBF was 63 ± 11 ml/(min 100 g) (mean ± SD). Nominal CBF from non-calibrated DSC-MRI was 277 ± 61 ml/(min 100 g), while calibrations resulted in 56 ± 23 ml/(min 100 g) (Bookend) and 52 ± 16 ml/(min 100 g) (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. 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.
    MAGMA Magnetic Resonance Materials in Physics Biology and Medicine 02/2014; 27(6). DOI:10.1007/s10334-014-0431-x · 2.87 Impact Factor
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    ABSTRACT: Purpose: Quantification of cerebral blood flow can be accomplished by model-free arterial spin labeling using the quantitative STAR labeling of arterial regions (QUASAR) sequence. The required deconvolution is normally based on block-circulant singular value decomposition (cSVD)/oscillation SVD (oSVD), an algorithm associated with nonphysiological residue functions and potential effects of arterial dispersion. The aim of this work was to amend this by implementing nonlinear stochastic regularization (NSR) deconvolution, previously used to retrieve realistic residue functions in dynamic susceptibility contrast MRI. Methods: To characterize the residue function in model-free arterial spin labeling, and possibly to improve absolute cerebral blood flow quantification, NSR was applied to deconvolution of QUASAR data. For comparison, SVD-based deconvolution was also employed. Residue function characteristics and cerebral blood flow values from 10 volunteers were obtained. Simulations were performed to support the in vivo results. Results: NSR was able to resolve realistic residue functions in contrast to the SVD-based methods. Mean cerebral blood flow estimates in gray matter were 36.6 ± 2.6, 28.6 ± 3.3, 40.9 ± 3.6, and 42.9 ± 3.9 mL/100 g/min for cSVD, oSVD, NSR, and NSR with correction for arterial dispersion, respectively. In simulations, the NSR-based perfusion estimates showed better accuracy than the SVD-based approaches. Conclusion: Perfusion quantification by model-free arterial spin labeling is evidently dependent on the selected deconvolution method, and NSR is a feasible alternative to SVD-based methods.
    Magnetic Resonance in Medicine 11/2013; 70(5). DOI:10.1002/mrm.24587 · 3.57 Impact Factor

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    ISMRM, Salt Lake City, USA; 04/2013
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    ABSTRACT: Using dynamic contrast-enhanced MRI (DCE-MRI), it is possible to estimate pharmacokinetic (PK) parameters that convey information about physiological properties, e.g., in tumors. In DCE-MRI, errors propagate in a nontrivial way to the PK parameters. We propose a method based on multivariate linear error propagation to calculate uncertainty maps for the PK parameters. Uncertainties in the PK parameters were investigated for the modified Kety model. The method was evaluated with Monte Carlo simulations and exemplified with in vivo brain tumor data. PK parameter uncertainties due to noise in dynamic data were accurately estimated. Noise with standard deviation up to 15% in the baseline signal and the baseline T(1) map gave estimated uncertainties in good agreement with the Monte Carlo simulations. Good agreement was also found for up to 15% errors in the arterial input function amplitude. The method was less accurate for errors in the bolus arrival time with disagreements of 23%, 32%, and 29% for K(trans) , v(e) , and v(p) , respectively, when the standard deviation of the bolus arrival time error was 5.3 s. In conclusion, the proposed method provides efficient means for calculation of uncertainty maps, and it was applicable to a wide range of sources of uncertainty. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.
    Magnetic Resonance in Medicine 04/2013; 69(4). DOI:10.1002/mrm.24328 · 3.57 Impact Factor
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    ABSTRACT: Diffusion kurtosis imaging (DKI) is an emerging technique with the potential to quantify properties of tissue microstructure that may not be observable using diffusion tensor imaging (DTI). In order to help design DKI studies and improve interpretation of DKI results, we employed statistical power analysis to characterize three aspects of variability in four DKI parameters; the mean diffusivity, fractional anisotropy, mean kurtosis, and radial kurtosis. First, we quantified the variability in terms of the group size required to obtain a statistical power of 0.9. Second, we investigated the relative contribution of imaging and post-processing noise to the total variance, in order to estimate the benefits of longer scan times versus the inclusion of more subjects. Third, we evaluated the potential benefit of including additional covariates such as the size of the structure when testing for differences in group means. The analysis was performed in three major white matter structures of the brain: the superior cingulum, the corticospinal tract, and the mid-sagittal corpus callosum, extracted using diffusion tensor tractography and DKI data acquired in a healthy cohort. The results showed heterogeneous variability across and within the white matter structures. Thus, the statistical power varies depending on parameter and location, which is important to consider if a pathogenesis pattern is inferred from DKI data. In the data presented, inter-subject differences contributed more than imaging noise to the total variability, making it more efficient to include more subjects rather than extending the scan-time per subject. Finally, strong correlations between DKI parameters and the structure size were found for the cingulum and corpus callosum. Structure size should thus be considered when quantifying DKI parameters, either to control for its potentially confounding effect, or as a means of reducing unexplained variance.
    NeuroImage 03/2013; 76(1). DOI:10.1016/j.neuroimage.2013.02.078 · 6.36 Impact Factor
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    ABSTRACT: Purpose To provide estimates of the diffusional kurtosis in the healthy brain in anatomically defined areas and list these along previously reported values in pathologies. Materials and Methods Thirty-six volunteers (mean age = 33.1 years; range, 19–64 years) underwent diffusional kurtosis imaging. Mean kurtosis (MK), radial kurtosis (RK), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA) were determined in 26 anatomical structures. Parameter estimates were assessed regarding age dependence. Results MK varied from 1.38 in the splenium of the corpus callosum to 0.66 in the caudate head, MD varied from 0.68 to 0.62 μm2/ms and FA from 0.87 to 0.29. MK, and FA showed a strong positive correlation, RK and RD a strong negative correlation. Parameter estimates showed age correlation in some regions; also the average MK and RK for all WM and all GM areas, respectively, were negatively correlated with age. Conclusion DKI parameter estimates MK and RK varied depending on the anatomical region and varied with age in pooled WM and GM data. MK estimates in the internal capsule, corpus callosum, and thalamus were consistent with previous studies. The range of values of MK and RK in healthy brain overlapped with that in pathologies. J. Magn. Reson. Imaging 2013;37:610–618. © 2012 Wiley Periodicals, Inc.
    Journal of Magnetic Resonance Imaging 03/2013; 37(3). DOI:10.1002/jmri.23857 · 3.21 Impact Factor
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    ABSTRACT: Purpose: To evaluate whether a non-linear blood ΔR2*-versus-concentration relationship improves quantitative cerebral blood flow (CBF) estimates obtained by dynamic susceptibility contrast (DSC) MRI in a comparison with Xe-133 SPECT CBF in healthy volunteers. Material and methods: Linear as well as non-linear relationships between ΔR2* and contrast agent concentration in blood were applied to the arterial input function (AIF) and the venous output function (VOF) from DSC-MRI. To reduce partial volume effects in the AIF, the arterial time integral was rescaled using a corrected VOF scheme. Results: Under the assumption of proportionality between the two modalities, the relationship CBF(MRI)=0.58CBF(SPECT) (r=0.64) was observed using the linear relationship and CBF(MRI)=0.51CBF(SPECT) (r=0.71) using the non-linear relationship. Discussion: A smaller ratio of the VOF time integral to the AIF time integral and a somewhat better correlation between global DSC-MRI and Xe-133 SPECT CBF estimates were observed using the non-linear relationship. The results did not, however, confirm the superiority of one model over the other, potentially because realistic AIF signal data may well originate from a combination of blood and surrounding tissue.
    Magnetic Resonance Imaging 01/2013; 31(5). DOI:10.1016/j.mri.2012.12.001 · 2.09 Impact Factor
  • André Ahlgren · Ronnie Wirestam · Freddy Ståhlberg · Linda Knutsson ·

    ESMRMB 2013, Toulouse, France; 01/2013
  • Ronnie Wirestam ·
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    ABSTRACT: Tracer kinetic modeling for quantification of perfusion and capillary wall permeability is a well-established approach, applied to various imaging modalities. In this review, methods employing intravascular as well as diffusible nonradioactive contrast agents for characterization of tissue microcirculation and microvasculature are described. The article focuses on perfusion and permeability imaging by MRI, particularly for brain applications, and the use of alternative medical imaging methods, such as CT and ultrasound, is also briefly introduced.
    Imaging in medicine 08/2012; 4(4):423-442. DOI:10.2217/iim.12.24
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    ISMRM, Melbourne, Australia; 05/2012

  • ESMRMB 2012, Lisbon, Portugal; 01/2012

Publication Stats

1k Citations
196.30 Total Impact Points


  • 1991-2015
    • Lund University
      • • Department of Medical Radiation Physics
      • • Department of Diagnostic Radiology
      • • Department of Radiation Physics
      Lund, Skåne, Sweden
  • 1995
    • Copenhagen University Hospital Hvidovre
      Hvidovre, Capital Region, Denmark
  • 1992
    • Karolinska University Hospital
      Tukholma, Stockholm, Sweden