Cartesian SENSE and k-t SENSE reconstruction using commodity graphics hardware.

This study demonstrates that modern commodity graphics cards (GPUs) can be used to perform fast Cartesian SENSE and k-t SENSE reconstruction. Specifically, the SENSE inversion is accelerated by up to two orders of magnitude and is no longer the time-limiting step. The achieved reconstruction times are now well below the acquisition times, thus enabling real-time, interactive SENSE imaging, even with a large number of receive coils. The fast GPU reconstruction is also beneficial for datasets that are not acquired in real time. We demonstrate that it can be used for interactive adjustment of regularization parameters for k-t SENSE in the same way that one would adjust window and level settings. This enables a new way of performing imaging reconstruction, where the user chooses the setting of tunable reconstruction parameters, in real time, depending on the context in which the images are interpreted.     

Measuring bone mineral density with fat–water MRI: comparison with computed tomography

Purpose:

To develop a method for measuring bone mineral density (BMD) with MRI, and to validate this method against quantitative computed tomography (QCT).

Materials and Methods:

A mathematical relationship between signal intensities from proton‐density‐weighted in‐phase images generated by multi‐fat‐peak T‐IDEAL MRI and BMD was derived using a set of calibration standards constructed from various concentrations of hydroxyapatite in water. Using these standards, the relationship between hydroxyapatite concentration and MRI signal intensity was examined. A T‐IDEAL protocol was performed on the patella of 5 volunteers and the signal model was used to compute BMD of all voxels of the patella. The BMD data were validated by obtaining QCT scans of the same patella, computing QCT BMD of all voxels, and comparing the MRI and QCT BMD data by performing linear regression analysis on a voxel‐by‐voxel basis.

Results:

A strong linear correlation between hydroxyapatite concentration of the calibration standards and MRI signal intensities was observed (r = 0.98; P < 0.01). In the patella, BMD measurements (N = 28796 voxels) from the MRI signal model were significantly correlated with those from QCT (r = 0.82; P < 0.001; slope = 1.02; and intercept = ?0.26).

Conclusion:

A standardized phantom consisting of hydroxyapatite and water can be used to accurately quantify BMD in vivo using MRI. J. Magn. Reson. Imaging 2013;37:237–242. © 2012 Wiley Periodicals, Inc.

     

Improved fat suppression using multipeak reconstruction for IDEAL chemical shift fat‐water separation: Application with fast spin echo imaging

Purpose

To evaluate and quantify improvements in the quality of fat suppression for fast spin‐echo imaging of the knee using multipeak fat spectral modeling and IDEAL fat‐water separation.

Materials and Methods

T₁‐weighted and T₂‐weighted fast spin‐echo sequences with IDEAL fat‐water separation and two frequency‐selective fat‐saturation methods (fat‐selective saturation and fat‐selective partial inversion) were performed on 10 knees of five asymptomatic volunteers. The IDEAL images were reconstructed using a conventional single‐peak method and precalibrated and self‐calibrated multipeak methods that more accurately model the NMR spectrum of fat. The signal‐to‐noise ratio (SNR) was measured in various tissues for all sequences. Student t‐tests were used to compare SNR values.

Results

Precalibrated and self‐calibrated multipeak IDEAL had significantly greater suppression of signal (P < 0.05) within subcutaneous fat and bone marrow than fat‐selective saturation, fat‐selective partial inversion, and single‐peak IDEAL for both T₁‐weighted and T₂‐weighted fast spin‐echo sequences. For T₁‐weighted fast spin‐echo sequences, the improvement in the suppression of signal within subcutaneous fat and bone marrow for multipeak IDEAL ranged between 65% when compared to fat‐selective partial inversion to 86% when compared to fat‐selectivesaturation. For T2‐weighted fast spin‐echo sequences, the improvement for multipeak IDEAL ranged between 21% when compared to fat‐selective partial inversion to 81% when compared to fat‐selective saturation.

Conclusion

Multipeak IDEAL fat‐water separation provides improved fat suppression for T₁‐weighted and T₂‐weighted fast spin‐echo imaging of the knee when compared to single‐peak IDEAL and two widely used frequency‐selected fat‐saturation methods. J. Magn. Reson. Imaging 2009;29:436–442. © 2009 Wiley‐Liss, Inc.     

Turboprop IDEAL: A motion‐resistant fat–water separation technique

Suppression of the fat signal in MRI is very important for many clinical applications. Multi‐point water–fat separation methods, such as IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least‐squares estimation), can robustly separate water and fat signal, but inevitably increase scan time, making separated images more easily affected by patient motions. PROPELLER (Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction) and Turboprop techniques offer an effective approach to correct for motion artifacts. By combining these techniques together, we demonstrate that the new TP‐IDEAL method can provide reliable water–fat separation with robust motion correction. The Turboprop sequence was modified to acquire source images, and motion correction algorithms were adjusted to assure the registration between different echo images. Theoretical calculations were performed to predict the optimal shift and spacing of the gradient echoes. Phantom images were acquired, and results were compared with regular FSE‐IDEAL. Both T1‐ and T2‐weighted images of the human brain were used to demonstrate the effectiveness of motion correction. TP‐IDEAL images were also acquired for pelvis, knee, and foot, showing great potential of this technique for general clinical applications. Magn Reson Med 61:188–195, 2009. © 2008 Wiley‐Liss, Inc.     

Identification of brown adipose tissue in mice with fat–water IDEAL‐MRI

Purpose:

To investigate the feasibility of using IDEAL (Iterative Decomposition with Echo Asymmetry and Least squares estimation) fat–water imaging and the resultant fat fraction metric in detecting brown adipose tissue (BAT) in mice, and in differentiating BAT from white adipose tissue (WAT).

Materials and Methods:

Excised WAT and BAT samples and whole‐mice carcasses were imaged with a rapid three‐dimensional fat–water IDEAL‐SPGR sequence on a 3 Tesla scanner using a single‐channel wrist coil. An isotropic voxel size of 0.6 mm was used. Excised samples were also scanned with single‐voxel proton spectroscopy. Fat fraction images from IDEAL were reconstructed online using research software, and regions of WAT and BAT were quantified.

Results:

A broad fat fraction range for BAT was observed (40–80%), in comparison to a tighter and higher WAT range of 90–93%, in both excised tissue samples and in situ. Using the fat fraction metric, the interscapular BAT depot in each carcass could be clearly identified, as well as peri‐renal and inguinal depots that exhibited a mixed BAT and WAT phenotype appearance.

Conclusion:

Due to BAT's multi‐locular fat distribution and extensive mitochondrial, cytoplasm, and vascular supply, its fat content is significantly less than that of WAT. We have demonstrated that the fat fraction metric from IDEAL‐MRI is a sensitive and quantitative approach to noninvasively characterize BAT. J. Magn. Reson. Imaging 2010;31:1195–1202. © 2010 Wiley‐Liss, Inc.     

Online real‐time reconstruction of adaptive TSENSE with commodity CPU/GPU hardware

Adaptive temporal sensitivity encoding (TSENSE) has been suggested as a robust parallel imaging method suitable for MR guidance of interventional procedures. However, in practice, the reconstruction of adaptive TSENSE images obtained with large coil arrays leads to long reconstruction times and latencies and thus hampers its use for applications such as MR‐guided thermotherapy or cardiovascular catheterization. Here, we demonstrate a real‐time reconstruction pipeline for adaptive TSENSE with low image latencies and high frame rates on affordable commodity personal computer hardware. For typical image sizes used in interventional imaging (128 × 96, 16 channels, sensitivity encoding (SENSE) factor 2‐4), the pipeline is able to reconstruct adaptive TSENSE images with image latencies below 90 ms at frame rates of up to 40 images/s, rendering the MR performance in practice limited by the constraints of the MR acquisition. Its performance is demonstrated by the online reconstruction of in vivo MR images for rapid temperature mapping of the kidney and for cardiac catheterization. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.     

Combination of complex‐based and magnitude‐based multiecho water‐fat separation for accurate quantification of fat‐fraction

Multipoint water–fat separation techniques rely on different water–fat phase shifts generated at multiple echo times to decompose water and fat. Therefore, these methods require complex source images and allow unambiguous separation of water and fat signals. However, complex‐based water–fat separation methods are sensitive to phase errors in the source images, which may lead to clinically important errors. An alternative approach to quantify fat is through “magnitude‐based” methods that acquire multiecho magnitude images. Magnitude‐based methods are insensitive to phase errors, but cannot estimate fat‐fraction greater than 50%. In this work, we introduce a water–fat separation approach that combines the strengths of both complex and magnitude reconstruction algorithms. A magnitude‐based reconstruction is applied after complex‐based water–fat separation to removes the effect of phase errors. The results from the two reconstructions are then combined. We demonstrate that using this hybrid method, 0–100% fat‐fraction can be estimated with improved accuracy at low fat‐fractions. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.     

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): Fat/Water separation at 7 tesla

Purpose:

To reduce swaps in fat–water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map.

Materials and Methods:

Fat–water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi‐point Dixon model. The B0 field maps were processed with a novel hole‐filling method, based on edge strength between regions, and a novel k‐means method, based on field‐map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction.

Results:

Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic.

Conclusion:

Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. J. Magn. Reson. Imaging 2013;37:1247–1253. © 2012 Wiley Periodicals, Inc.     

Regularized iterative reconstruction for undersampled BLADE and its applications in three‐point Dixon water–fat separation

In MRI, the suppression of fat signal is very important for many applications. Multipoint Dixon based water–fat separation methods are commonly used due to its robustness to B₀ homogeneity compared with other fat suppression methods, such as spectral fat saturation. The traditional Cartesian k‐space trajectory based multipoint Dixon technique is sensitive to motion, such as pulsatile blood flow, resulting in artifacts that compromise image quality. This work presents a three‐point Dixon water–fat separation method using undersampled BLADE (aka PROPELLER) for motion robustness and speed. A regularized iterative reconstruction method is then proposed for reducing the streaking artifacts coming from undersampling. In this study, the performance of the regularized iterative reconstruction method is first tested by simulations and on MR phantoms. The performance of the proposed technique is then evaluated in vivo by comparing it with conventional fat suppression methods on the human brain and knee. Experiments show that the presented method delivers reliable water–fat separation results. The reconstruction method suppresses streaking artifacts typical for undersampled BLADE acquisition schemes without missing fine structures in the image. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.