Clason, Christian

Knoll, Florian

Kraiger, Markus

Stollberger, Rudolf

TUGraz OPEN Library

Assessment of Iterative Regularized Parallel Imaging Reconstruction for Quantitative Magnetic Resonance Imaging  M. Kraiger1, F. Knoll1, C. Clason2 and R. Stollberger11Graz University of Technology, Institute of Medical Engineering, Graz, Austria 2University of Graz, Institute for Mathematics and Scientific Computing, Graz, Austria mkraiger@student.tugraz.at Kurzfassung  Mit nicht linearer paralleler Bildrekonstruktion unter Verwendung iterativ regularisierter Gauss Newton Methoden (IRGN) konnten besonders hohe Beschleunigungsfaktoren bei der MR Bildgebung erzielt werden. Bei dieser Technik werden die Daten mit Arrayspulen aufgenommen und sowohl die Spulensensitivitäten als auch das Bild aus den unterab-getasteten Daten berechnet. Für die Bildrekonstruktion ist es notwendig verschiedene Normalisierungsschritte für jedes Bild und jede Empfangsspule durchzuführen. Im Rahmen diese Arbeit wurde untersucht ob es durch den komplexen Re-konstruktionsvorgang zu Einschränkungen bei der Anwendung des Verfahrens für die quantitative Bestimmung von NMR-Parametern (T2) kommt. Dafür wurden Messungen mit voller Kodierung mit dem etablierten Parallelimagingver-fahren „Grappa“ und mit der IRGN Rekonstruktion verglichen. Es zeigte sich, das beide Parallelimagingverfahren für quantitative Auswertungen grundsätzlich geeignet sind. Für die verwendete kartesische Bildkodierung konnten gewisse Vorteile der IRGN Rekonstruktion in Bereichen mit geringem SNR im Vergleich zur verwendeten „Grappa“ Implemen-tierung gefunden werden. Für eine radiale k-Raum Abtastung sind weitere Untersuchungen notwendig. AbstractNonlinear parallel imaging reconstruction using an iterative regularized Gauss Newton method (IRGN) has shown its potential in several applications. This technique acquires data using array coils were the coil sensitivites and the image are both computed from the under sampled data. Several normalization steps for each image and each receiver coil are necessary prior image reconstruction. In the current work it was examined if the complex reconstruction process limits the applicability of this method for quantitative determination of NMR parameters (T2). Hence measurements with full encoding using the established parallel imaging method „Grappa“ were compared with the IRGN reconstruction. It was shown that both parallel imaging techniques are in principle applicable for quantitative determination. In the case of the applied cartesian image encoding certain advantages of the IRGN reconstruction in comparison to the applied „Grappa“ implementation were found in areas with low SNR.  Further examinations are necessary for radial k-space sampling. 1 Introduction The concept of conventional parallel MRI is based on the fact that the spatial receiver sensitivities are utilized for image generation, since the contribution of a signal source varies with its relative position to the receiver coil. The combination of Fourier phases encoding steps and the spa-tial information provided by the coil sensitivity distribution of the receiver coil arrays allows the reconstruction of MR-images from basically under sampled data. Hence spatial encoding can be performed more efficiently. Nowadays parallel imaging techniques are widely used in different applications of MRI [1]. The various implementa-tions can be generally divided into two groups. Depending whether the coil sensitivities can be directly determined during the process of image reconstruction from the under-sampled data or an additional scan is necessary for their computation. The recent developed iterative regularized Gauss Newton method (IRGN) [2] for parallel imaging determines both the coil sensitivities and the image from undersampled multi-coil data. The numerical implementation of this so-phisticated method is computationally demanding but it allows for specific applications very high accelerating fac-tors [3,4].  In this study it was investigated if this type of reconstruc-tion is applicable for quantitative imaging despite the complex reconstruction including image individual nor-malization. For that purpose high resolution multi-echo imaging with different acceleration factors was used for the quantification of the transverse relaxation time (T2). 2 Methods Three multi Spin-Echo (SE) datasets from  phantoms and a healthy volunteer were acquired on a clinical 3T scanner with different acceleration factors (fully sampled, AF=2 and AF=4). One phantom consisted of 6 water samples with varying Gd-DTPA (Magnevist®) concentration rang-ing between 0.95 and 6.7 mM. A second experiment using a homogeneous water phantom filled with 6.8mM Gd-DOTA (Dotarem®) was carried out to examine the recon-struction performance in low SNR regime. Scanning pa-rameters were TR=1800 ms, 10 echos, 150 mm FOV, 256x256 matrix, 10 slices, echo spacing=20/9.2 ms, slice thickness=5/2 mm for the phantom/in vivo respectively. In )PVTLK;LJO":\WWSI`>HS[LYKL.Y\`[LY)LYSPU5L^@VYR+60)4;Brought to you by | Technische Universität GrazAuthenticatedDownload Date | 3/29/17 2:50 PMvivo measurements were performed with a 8Ch tx/rx knee coil  while the water samples and the homogenous phan-tom were imaged with a 32Ch tx/rx and 12 Ch rx head coil respectively. In order to estimate the coil sensitivities 24 parallel imaging reference lines were used in the Cartesian k-space. Subsequent rawdata were exported from the scan-ner, and offline reconstructed using the IRGN method.  The T2 maps were computed using monoexponential lin-ear least squares curve fitting on a pixel-by-pixel basis. The initial spin-echo was excluded from the fitting proce-dure to minimize artifacts in the T2 calculation due to non-ideal slice profile or B1-inhomogeneities [5]. Echo signals below the noise level at longer echo times were discarded. For the water samples, ROIs were manually placed over each probe in the T2 maps of the central slice. In the ho-mogenous phantom four ROIs were placed at the border and one centre.  In the in-vivo case the  ROIs were manu-ally placed in a homogeneous region of the specific tissue. 3 Results The resulting reconstructed images of the in vivo meas-urement and the first phantom data acquired without accel-eration using sum of squares (SOS) and with AF=2, 4 us-ing IRGN are shown in figure 1. The reconstructions show that the image quality of all accelerated scans is visually comparable to the fully sampled data. No residual aliasing artifacts or local noise amplification were observed up to AF=4.  Figure 1 Representative images of different reconstruction techniques for different acceleration factors. In the phantom case, using an echo spacing of 20 ms,  the increase of the noise level in low signal regimes due to the inherent noise characteristic of the SOS reconstruction [6,7] pretended signal in dark areas of the reconstructed image. In contrary the additional noise level introduced in low signal areas usig IRGN was less dominant. A conse-quence of the weighting operation of the reconstructed im-ages at each echo time with their SOS of the current coil sensitivites [2]. This different signal characteristic was most prominent for sample #6. The mean signal time courses originating from a circular ROI place in sample #6 for both reconstructions are depicted in figure 2. Additionally the mean signal from a rectangular ROI placed in the background is given.  Figure 2 Comparison of the signal time course of sample #6 and background for the SOS and IRGN reconstruction. The resulting T2 maps of the different tissues for the dif-ferent acceleration factors are shown in figure 3.  Figure 3 Corresponding T2 maps for different acceleration factors, concentrations are given in mM. At an acceleration factor of 4 the general noise enhance-ment introduces noisier T2 maps compared to the fully sampled data, still the relaxation times are in agreement with literature values [8,9]. The resulting T2 maps of the phantom are shown in figure 3, mean T2 values of the different tissues  and the phan-toms are shown in figure 4. Error bars represent the stan-dard deviation (SD).  Figure 4 Comparison of the T2 values from the different reconstruction methods. The comparison of the mean values show that the relaxa-tion times computed from the accelerated IRGN scans lie in the interval mean ± SD of the fully sampled SOS data.  Brought to you by | Technische Universität GrazAuthenticatedDownload Date | 3/29/17 2:50 PMResulting T2 maps of the homogeneous phantom obtained from the IRGN at different acceleration factors are shown in figure 5. Additionally for comparison reason a T2 map obtained from GRAPPA with AF=4 is depicted as well.  Figure 5 Comparison of the spatial varying T2 values in homogeneous phantom at different AF and reconstruction methods, phase encoding: L-> R. Up to  an accelearation factor of 2 the resulting T2 values in the entire phantom can be considered as reliable T2 es-timates. In the challenging area at the phantom´s center (table 1, ROI 5), where the sensitivities of the different coils overlapped, hence less independent coil information was available, both algorithms yielded corrupted T2 esti-mates when using four fold under sampling.  Table 1 Comparison of the T2 values from homogenous phantom for the different reconstructions, T2 given in ms. With AF=4  the IRGN  technique showed in the outer re-gions superior reconstruction results than GRAPPA. This was confirmed by evaluating the resulting T2 values in the corresponding ROI. Results are given in table 1, demon-strating higher mean values and increased standard devia-tions of T2 obtained by using GRAPPA. 4 DiscussionIn this study we successfully demonstrated that nonlinear parallel imaging IRGN is applicable to quantitative MRI. Compared to conventional parallel imaging techniques, which apply SOS for combining the individual recon-structed coil images, IRGN does not produce a noise re-lated signal bias. This might be a specific advantage for diffusion weighted imaging using high b-factors.  The experiment with the homogenous phantom revealed the common limits of parallel reconstruction techniques including IRGN, where with increasing acceleration fac-tors the SNR drops and the uncertainty of the determined T2 increases. At high acceleration IRGN showed at the border regions of a homogeneous the phantom a better per-formance as GRAPPA. Besides the computational requirements of IRGN its at-tenuated noise level increase makes it a valuable alterna-tive to conventional parallel imaging, especially in low SNR regime. Future work will be targeted on modelling a formalism of the noise characteristic of IRGN equivalent to the g-factor. For radial k-space sampling it is expected that the performance of the IRGN reconstruction is even better but it must be investigated additionally. This work is supported by SFB F3209-18. 5 References [1] Larkman D et al.: Parallel magnetic resonance imag-ing. Physics in Medicine and Biology (2007) 52, R15-R55  [2] Uecker M et al.: Image reconstruction by regularized nonlinear inversion - Joint estimation of coil sensitivi-ties and image content. Magnetic Resonance in Medi-cine (2008) 60, p. 674-682 [3] Knoll F et al.: Improved reconstruction in non-cartesian parallel imaging by regularized nonlinear in-version. Proc Int Soc Magn Reson Med (2009) 17th Annu Meet [4] Kraiger M et al.: Quantification of transversal relaxa-tion time T2 using an iterative regularized parallel im-aging reconstruction. Proc Int Soc Magn Reson Med (2010),  18th Annu Meet   [5]Rubenstein JD et al.: Effects of compression and re-covery on bovine articular cartilage: appearance on MR images. Radiology (1996) 201, p. 843-850 [6]Hardy PA et al.: Calculating T2 in images from a phased array receiver. Magnetic Resonance in Medi-cine (2009) 61, p. 962-969 [7] Constantinides CD et al.: Signal-to-noise measure-ments in magnitude images from nmr phased arrays. Magnetic Resonance in Medicine (1997) 38, p. 852-857 [8]Mosher TJ et al.: MR imaging and T2 mapping of femoral cartilage: in vivo determination of the magic angle effect. American Journal of Roentgenology (2001) 177, p. 665-669 [9]Gold G et al.: Musculoskeletal MRI at 3.0T: relaxation times and image conrast. American Journal of Roent-genology  (2004) 183, p 343-351 Brought to you by | Technische Universität GrazAuthenticatedDownload Date | 3/29/17 2:50 PM

Assessment of Iterative Regularized Parallel Imaging Reconstruction for Quantitative Magnetic Resonance Imaging

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Assessment of Iterative Regularized Parallel Imaging Reconstruction for Quantitative Magnetic Resonance Imaging

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