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- Ahlgren, André, et al.
(författare)
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A linear mixed perfusion model for tissue partial volume correction of perfusion estimates in dynamic susceptibility contrast MRI: : Impact on absolute quantification, repeatability, and agreement with pseudo-continuous arterial spin labeling
- 2017
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 1522-2594 .- 0740-3194. ; 77:6, s. 2203-2214
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: The partial volume effect (PVE) is an important source of bias in brain perfusion measurements. The impact of tissue PVEs in perfusion measurements with dynamic susceptibility contrast MRI (DSC-MRI) has not yet been well established. The purpose of this study was to suggest a partial volume correction (PVC) approach for DSC-MRI and to study how PVC affects DSC-MRI perfusion results.METHODS: A linear mixed perfusion model for DSC-MRI was derived and evaluated by way of simulations. Twenty healthy volunteers were scanned twice, including DSC-MRI, arterial spin labeling (ASL), and partial volume measurements. Two different algorithms for PVC were employed and assessed.RESULTS: Simulations showed that the derived model had a tendency to overestimate perfusion values in voxels with high fractions of cerebrospinal fluid. PVC reduced the tissue volume dependence of DSC-MRI perfusion values from 44.4% to 4.2% in gray matter and from 55.3% to 14.2% in white matter. One PVC method significantly improved the voxel-wise repeatability, but PVC did not improve the spatial agreement between DSC-MRI and ASL perfusion maps.CONCLUSION: Significant PVEs were found for DSC-MRI perfusion estimates, and PVC successfully reduced those effects. The findings suggest that PVC might be an important consideration for DSC-MRI applications. Magn Reson Med, 2016. © 2016 Wiley Periodicals, Inc.
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| 4. |
- Ahlgren, André, et al.
(författare)
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Improved calculation of the equilibrium magnetization of arterial blood in arterial spin labeling
- 2018
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 1522-2594 .- 0740-3194. ; 80:5, s. 2223-2231
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To propose and assess an improved method for calculating the equilibrium magnetization of arterial blood ( M0a), used for calibration of perfusion estimates in arterial spin labeling.METHODS: Whereas standard M0a calculation is based on dividing a proton density-weighted image by an average brain-blood partition coefficient, the proposed method exploits partial-volume data to adjust this ratio. The nominator is redefined as the magnetization of perfused tissue, and the denominator is redefined as a weighted sum of tissue-specific partition coefficients. Perfusion data were acquired with a pseudo-continuous arterial spin labeling sequence, and partial-volume data were acquired using a rapid saturation recovery sequence with the same readout module. Results from 7 healthy volunteers were analyzed and compared with the conventional method.RESULTS: The proposed method produced improved M0a homogeneity throughout the brain in all subjects. The mean gray matter perfusion was significantly higher with the proposed method compared with the conventional method: 61.2 versus 56.3 mL/100 g/minute (+8.7%). Although to a lesser degree, the corresponding white matter values were also significantly different: 20.8 versus 22.0 mL/100 g/minute (-5.4%). The spatial and quantitative differences between the 2 methods were similar in all subjects.CONCLUSION: Compared with the conventional approach, the proposed method produced more homogenous M0a maps, corresponding to a more accurate calibration. The proposed method also yielded significantly different perfusion values across the whole brain, and performed consistently in all subjects. The new M0a method improves quantitative perfusion estimation with arterial spin labeling, and can therefore be of considerable value in perfusion imaging applications.
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| 5. |
- Ahlgren, André
(författare)
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Methodological improvements in quantitative MRI : Perfusion estimation and partial volume considerations
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The magnetic resonance imaging (MRI) scanner is a remarkable medical imaging device, capable of producing detailed images of the inside of the body. In addition to imaging internal tissue structures, the scanner can also be used to measure various properties of the tissue. If a tissue property is measured in every image pixel, the resulting property image (the parameter map) can be displayed and used for medical interpretation — a concept referred to as ‘quantitative MRI’. Tissue properties that are commonly probed include traditional MR parameters such as T1, T2 and proton density, as well as functional parameters such as tissue perfusion, brain activation, diffusion and flow.Quantitative MRI relies on the continuous development of new and improved ways to acquire data with the scanner (pulse sequences), to model and analyze the data (postprocessing), and to interpret the output from a medical perspective. This thesis describes methods that have been developed with the specific aim to improve certain quantitative MRI techniques. In particular, the work is focused on improved analysis of perfusion MRI data, and ways to handle the partial volume issue.Constant delivery of oxygen and nutrients via the blood is vital for tissue viability. Perfusion MRI is designed to measure the properties of the local blood delivery, and perfusion images can be used as a marker for tissue health. Whereas rough estimates of perfusion properties can suffice in some cases, more accurate information can provide improved medical research and diagnostics. Most of the methods described in this work aim to provide tissue perfusion information with higher accuracy than previous approaches.One particular way to improve perfusion information is to account for the so-called partial volume effect. This means that limited image resolution implies that a single pixel may contain signal from more than one type of tissue. In other words, the signal can be mixed, and the calculated perfusion represents a mixture of the underlying perfusion of the different tissue types. By first using another quantitative MRI method that estimates the partial volume of each tissue type in every pixel (referred to as partial volume mapping), the partial volume effect can be corrected for by so-called partial volume correction.Partial volume mapping also relates to the field of MRI segmentation, that is, methods to segment an image into different tissue types and anatomical regions. This work also explores and expands a new partial volume mapping and segmentation method, referred to as fractional signal modeling, which seems to be exceptionally versatile and robust, as well as simple to implement and use. A general framework is laid out, with the hope of inspiring more researchers to adapt it and assess its value in different applications.In conclusion, this work improved the quantification in different perfusion MRI methods, as well as presented a new partial volume mapping method. The described methods will hopefully yield value in medical applications in the future.
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| 6. |
- Ahlgren, André, et al.
(författare)
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Partial volume correction of brain perfusion estimates using the inherent signal data of time-resolved arterial spin labeling.
- 2014
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480. ; 27:9, s. 1112-1122
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Tidskriftsartikel (refereegranskat)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.
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| 7. |
- Ahlgren, André, et al.
(författare)
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Perfusion quantification by model-free arterial spin labeling using nonlinear stochastic regularization deconvolution.
- 2013
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Ingår i: Magnetic Resonance in Medicine. - : Wiley. - 1522-2594 .- 0740-3194. ; 70:5, s. 1470-1480
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Tidskriftsartikel (refereegranskat)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. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.
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| 8. |
- Ahlgren, André, et al.
(författare)
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Quantification of microcirculatory parameters by joint analysis of flow-compensated and non-flow-compensated intravoxel incoherent motion (IVIM) data.
- 2016
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Ingår i: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 29:5, s. 640-649
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Tidskriftsartikel (refereegranskat)abstract
- The aim of this study was to improve the accuracy and precision of perfusion fraction and blood velocity dispersion estimates in intravoxel incoherent motion (IVIM) imaging, using joint analysis of flow-compensated and non-flow-compensated motion-encoded MRI data. A double diffusion encoding sequence capable of switching between flow-compensated and non-flow-compensated encoding modes was implemented. In vivo brain data were collected in eight healthy volunteers and processed using the joint analysis. Simulations were used to compare the performance of the proposed analysis method with conventional IVIM analysis. With flow compensation, strong rephasing was observed for the in vivo data, approximately cancelling the IVIM effect. The joint analysis yielded physiologically reasonable perfusion fraction maps. Estimated perfusion fractions were 2.43 ± 0.81% in gray matter, 1.81 ± 0.90% in deep gray matter, and 1.64 ± 0.72% in white matter (mean ± SD, n = 8). Simulations showed improved accuracy and precision when using joint analysis of flow-compensated and non-flow-compensated data, compared with conventional IVIM analysis. Double diffusion encoding with flow compensation was feasible for in vivo imaging of the perfusion fraction in the brain. The strong rephasing implied that blood flowing through the cerebral microvascular system was closer to the ballistic limit than the diffusive limit. © 2016 The Authors NMR in Biomedicine published by John Wiley & Sons Ltd.
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| 10. |
- Beal, Jacob, et al.
(författare)
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Robust estimation of bacterial cell count from optical density
- 2020
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Ingår i: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Tidskriftsartikel (refereegranskat)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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