Liver MRI with amide proton transfer imaging: feasibility and accuracy for the characterization of focal liver lesions.

OBJECTIVE: To investigate the feasibility of using amide proton transfer (APT) magnetic resonance imaging (MRI) in the liver and to evaluate its ability to characterize focal liver lesions (FLLs). METHODS: A total of 203 patients with suspected FLLs who underwent APT imaging at 3T were included. APT imaging was obtained using a single-slice turbo spin-echo sequence to include FLLs through five breath-holds, and its acquisition time was approximately 1 min. APT signals in the background liver and FLL were measured with magnetization transfer ratio asymmetry (MTRasym) at 3.5 ppm. The technical success rate of APT imaging and the reasons for failure to obtain meaningful MTRasym values were assessed. The Mann Whitney U test was used to compare MTRasym values between different FLLs. RESULTS: The technical success rate of APT imaging in the liver was 62.1% (126/203). The reasons for failure were a too large B0 inhomogeneity (n = 43), significant respiratory motion (n = 12), and these two factors together (n = 22), respectively. Among 59 FLLs with analyzable APT images, MTRasym values were compared between 27 patients with liver metastases and 23 patients with hepatocellular carcinomas (HCCs). The MTRasym values of metastases were significantly higher than those of HCC (0.13 ± 2.15% vs. - 1.41 ± 3.68%, p = 0.027). CONCLUSIONS: APT imaging could be an imaging biomarker for the differentiation of FLLs. However, further technical improvement is required before APT imaging can be clinically applied to liver MRI. KEY POINTS: • Liver APT imaging was technically feasible, but with a relatively low success rate (62.1%). • Liver metastases showed higher APT values than hepatocellular carcinomas.

Technical Note: Clustering-based motion compensation scheme for multishot diffusion tensor imaging.

PURPOSE: To extend image reconstruction using image-space sampling function (IRIS) to address large-scale motion in multishot diffusion-weighted imaging (DWI). METHODS: A clustered IRIS (CIRIS) algorithm that would extend IRIS was proposed to correct for large-scale motion. For DWI, CIRIS initially groups the shots into clusters without intracluster large-scale motion and reconstructs each cluster by using IRIS. Then, CIRIS registers these cluster images and combines the registered images by using a weighted average to correct for voxel mismatch caused by intercluster large-scale motion. For diffusion tensor imaging (DTI), CIRIS further reduces the effect of motion on diffusion directions by treating motion-induced direction changes as additional diffusion directions. CIRIS also introduces the detection and rejection of motion-corrupted data to avoid corresponding image degradation. The proposed method was evaluated by simulation and in vivo diffusion datasets. RESULTS: Experiments demonstrated that CIRIS can reduce motion-induced blurring and artifacts in DWI and provide more accurate DTI estimations in the presence of large-scale motion, compared with IRIS. CONCLUSION: The proposed method presents a novel approach to correct for large-scale in-plane motion for multishot DWI and is expected to benefit the practical application of high-resolution diffusion imaging.

A comparison of readout segmented EPI and interleaved EPI in high-resolution diffusion weighted imaging.

PURPOSE: To provide a comprehensive understanding of multi-shot EPI diffusion imaging methods by comparing Readout segmented EPI (RS-EPI) and interleaved EPI (iEPI). MATERIALS AND METHODS: RS-EPI and iEPI were compared on the same 3T scanner. A 2D navigator was used for both RS-EPI and iEPI for phase correction. Signal to noise ratio (SNR), fractional anisotropy (FA) and distortion level were compared using phantom data. Distortion reduction capability and scan efficiency were compared with different protocols with simulations. In addition, distortion reduction capability and diffusion tensor imaging performance were compared using in vivo data. RESULTS: Our phantom data showed that the mean SNRs were 50.5, 86.6 and 45.4 for RS-EPI using GRAPPA=3, fully sampled iEPI and iEPI using GRAPPA=2 respectively. The mean FA values were 0.08, 0.05 and 0.09 for RS-EPI using GRAPPA=3, fully sampled iEPI and iEPI using GRAPPA=2 respectively. The distortion levels were 1.34mm, 1.29mm and 0.61mm for RS-EPI using GRAPPA=3, fully sampled iEPI and iEPI using GRAPPA=2 respectively. The effective echo spacing could be reduced by increasing the number of shots for both methods but more prominent for iEPI. The scan time was approximately proportional to the number of shots for both methods and RS-EPI showed a shorter scan time. Our in vivo data for distortion comparison showed consistent results with the effective echo spacing study. The mean difference of the FA and MD values between the high resolution sequences and SS-EPI was all within 7%. CONCLUSION: For high resolution diffusion imaging, iEPI has more potential in distortion reduction than RS-EPI when increasing the number of shots. RS-EPI can achieve a reasonable SNR with a shorter scan time than iEPI. RS-EPI and iEPI have similar performance in FA and MD quantifications as well as showing structure details when using eleven shots for in vivo diffusion tensor imaging.

Characterizing amide proton transfer imaging in haemorrhage brain lesions using 3T MRI.

OBJECTIVES: The aim of this study was to characterize amide proton transfer (APT)-weighted signals in acute and subacute haemorrhage brain lesions of various underlying aetiologies. METHODS: Twenty-three patients with symptomatic haemorrhage brain lesions including tumorous (n = 16) and non-tumorous lesions (n = 7) were evaluated. APT imaging was performed and analyzed with magnetization transfer ratio asymmetry (MTR asym ). Regions of interest were defined as the enhancing portion (when present), acute or subacute haemorrhage, and normal-appearing white matter based on anatomical MRI. MTR asym values were compared among groups and components using a linear mixed model. RESULTS: MTR asym values were 3.68 % in acute haemorrhage, 1.6 % in subacute haemorrhage, 2.65 % in the enhancing portion, and 0.38 % in normal white matter. According to the linear mixed model, the distribution of MTR asym values among components was not significantly different between tumour and non-tumour groups. MTR asym in acute haemorrhage was significantly higher than those in the other regions regardless of underlying pathology. CONCLUSIONS: Acute haemorrhages showed high MTR asym regardless of the underlying pathology, whereas subacute haemorrhages showed lower MTR asym than acute haemorrhages. These results can aid in the interpretation of APT imaging in haemorrhage brain lesions. KEY POINTS: • Acute haemorrhages show significantly higher MTR asym values than subacute haemorrhages. • MTR asym is higher in acute haemorrhage than in enhancing tumour tissue. • MTR asym in haemorrhage does not differ between tumorous and non-tumorous lesions.

Assessment of the patellofemoral cartilage: Correlation of knee pain score with magnetic resonance cartilage grading and magnetization transfer ratio asymmetry of glycosaminoglycan chemical exchange saturation transfer.

PURPOSE: Biochemical imaging of glycosaminoglycan chemical exchange saturation transfer (gagCEST) could predict the depletion of glycosaminoglycans (GAG) in early osteoarthritis. The purpose of this study was to evaluate the relationship between the magnetization transfer ratio asymmetry (MTRasym) of gagCEST images and visual analog scale (VAS) pain scores in the knee joint. MATERIALS AND METHODS: This retrospective study was approved by the institutional review board. A phantom study was performed using hyaluronic acid to validate the MTRasym values of gagCEST images. Knee magnetic resonance (MR) images of 22 patients (male, 9; female, 13; mean age, 50.3years; age range; 25-79years) with knee pain were included in this study. The MR imaging (MRI) protocol involved standard knee MRI as well as gagCEST imaging, which allowed region-of-interest analyses of the patellar facet and femoral trochlea. The MTRasym at 1.0ppm was calculated at each region. The cartilages of the patellar facets and femoral trochlea were graded according to the Outerbridge classification system. Data regarding the VAS scores of knee pain were collected from the electronic medical records of the patients. Statistical analysis was performed using Spearman's correlation. RESULTS: The results of the phantom study revealed excellent correlation between the MTRasym values and the concentration of GAGs (r=0.961; p=0.003). The cartilage grades on the MR images showed significant negative correlation with the MTRasym values in the patellar facet and femoral trochlea (r=-0.460; p=0.031 and r=-0.543; p=0.009, respectively). The VAS pain scores showed significant negative correlation with the MTRasym values in the patellar facet and femoral trochlea (r=-0.435; p=0.043 and r=-0.671; p=0.001, respectively). CONCLUSION: The pain scores were associated with the morphological and biochemical changes in articular cartilages visualized on knee MR images. The biochemical changes, visualized in terms of the MTRasym values of the gagCEST images, exhibited greater correlation with the pain scores than the morphological changes visualized on conventional MR images; these results provide evidence supporting the theory regarding the association of patellofemoral osteoarthritis with knee pain scores.

Effects of MR parameter changes on the quantification of diffusion anisotropy and apparent diffusion coefficient in diffusion tensor imaging: evaluation using a diffusional anisotropic phantom.

OBJECTIVE: To validate the usefulness of a diffusional anisotropic capillary array phantom and to investigate the effects of diffusion tensor imaging (DTI) parameter changes on diffusion fractional anisotropy (FA) and apparent diffusion coefficient (ADC) using the phantom. MATERIALS AND METHODS: Diffusion tensor imaging of a capillary array phantom was performed with imaging parameter changes, including voxel size, number of sensitivity encoding (SENSE) factor, echo time (TE), number of signal acquisitions, b-value, and number of diffusion gradient directions (NDGD), one-at-a-time in a stepwise-incremental fashion. We repeated the entire series of DTI scans thrice. The coefficients of variation (CoV) were evaluated for FA and ADC, and the correlation between each MR imaging parameter and the corresponding FA and ADC was evaluated using Spearman's correlation analysis. RESULTS: The capillary array phantom CoVs of FA and ADC were 7.1% and 2.4%, respectively. There were significant correlations between FA and SENSE factor, TE, b-value, and NDGD, as well as significant correlations between ADC and SENSE factor, TE, and b-value. CONCLUSION: A capillary array phantom enables repeated measurements of FA and ADC. Both FA and ADC can vary when certain parameters are changed during diffusion experiments. We suggest that the capillary array phantom can be used for quality control in longitudinal or multicenter clinical studies.

Improved diffusion tensor imaging of the optic nerve using multishot two-dimensional navigated acquisitions.

PURPOSE: A diffusion-weighted multishot echo-planar imaging approach combined with SENSE and a two-dimensional (2D) navigated motion correction was investigated as an alternative to conventional single-shot counterpart to obtain optic nerve images at higher spatial resolution with reduced artifacts. METHODS: Fifteen healthy subjects were enrolled in the study. Six of these subjects underwent a repeated acquisition at least 2 weeks after the initial scan session to address reproducibility. Both single-shot and multishot diffusion tensor imaging studies of the human optic nerve were performed with matched scan time. Effect of subject motions were corrected using 2D phase navigator during multishot image reconstruction. Tensor-derived indices from proposed multishot were compared against conventional single-shot approach. Image resolution difference, right-left optic nerve asymmetry, and test-retest reproducibility were also assessed. RESULTS: In vivo results of acquired multishot images and quantitative maps of diffusion properties of the optic nerve showed significantly reduced image artifacts (e.g., distortions and blurring), and the derived diffusion indices were comparable to those from other studies. Single-shot scans presented larger variability between right and left optic nerves than multishot scans. Multishot scans also presented smaller variations across scans at different time points when compared with single-shot counterparts. CONCLUSION: The multishot technique has considerable potential for providing improved information on optic nerve pathology and may also be translated to higher fields.

High-resolution human diffusion tensor imaging using 2-D navigated multishot SENSE EPI at 7 T.

The combination of parallel imaging with partial Fourier acquisition has greatly improved the performance of diffusion-weighted single-shot EPI and is the preferred method for acquisitions at low to medium magnetic field strength such as 1.5 or 3 T. Increased off-resonance effects and reduced transverse relaxation times at 7 T, however, generate more significant artifacts than at lower magnetic field strength and limit data acquisition. Additional acceleration of k-space traversal using a multishot approach, which acquires a subset of k-space data after each excitation, reduces these artifacts relative to conventional single-shot acquisitions. However, corrections for motion-induced phase errors are not straightforward in accelerated, diffusion-weighted multishot EPI because of phase aliasing. In this study, we introduce a simple acquisition and corresponding reconstruction method for diffusion-weighted multishot EPI with parallel imaging suitable for use at high field. The reconstruction uses a simple modification of the standard sensitivity-encoding (SENSE) algorithm to account for shot-to-shot phase errors; the method is called image reconstruction using image-space sampling function (IRIS). Using this approach, reconstruction from highly aliased in vivo image data using 2-D navigator phase information is demonstrated for human diffusion-weighted imaging studies at 7 T. The final reconstructed images show submillimeter in-plane resolution with no ghosts and much reduced blurring and off-resonance artifacts.

Integrating Medical Imaging Analyses through a High-throughput Bundled Resource Imaging System.

Exploitation of advanced, PACS-centric image analysis and interpretation pipelines provides well-developed storage, retrieval, and archival capabilities along with state-of-the-art data providence, visualization, and clinical collaboration technologies. However, pursuit of integrated medical imaging analysis through a PACS environment can be limiting in terms of the overhead required to validate, evaluate and integrate emerging research technologies. Herein, we address this challenge through presentation of a high-throughput bundled resource imaging system (HUBRIS) as an extension to the Philips Research Imaging Development Environment (PRIDE). HUBRIS enables PACS-connected medical imaging equipment to invoke tools provided by the Java Imaging Science Toolkit (JIST) so that a medical imaging platform (e.g., a magnetic resonance imaging scanner) can pass images and parameters to a server, which communicates with a grid computing facility to invoke the selected algorithms. Generated images are passed back to the server and subsequently to the imaging platform from which the images can be sent to a PACS. JIST makes use of an open application program interface layer so that research technologies can be implemented in any language capable of communicating through a system shell environment (e.g., Matlab, Java, C/C++, Perl, LISP, etc.). As demonstrated in this proof-of-concept approach, HUBRIS enables evaluation and analysis of emerging technologies within well-developed PACS systems with minimal adaptation of research software, which simplifies evaluation of new technologies in clinical research and provides a more convenient use of PACS technology by imaging scientists.

Characterizing fiber directional uncertainty in diffusion tensor MRI.

Image noise in diffusion tensor MRI (DT-MRI) causes errors in the measured tensor and hence variance in the estimated fiber orientation. Uncertainty in fiber orientation has been described using a circular "cone of uncertainty" (CU) around the principal eigenvector of the DT. The CU has proved to be a useful construct for quantifying and visualizing the variability of DT-MRI parameters and fiber tractography. The assumption of circularity of the CU has not been tested directly, however. In this work, bootstrap analysis and simple theoretical arguments were used to show that the CU is elliptical and multivariate normal in the vast majority of white matter (WM) voxels for typical measurement conditions. The dependence of the cone angle on the signal-to-noise ratio (SNR) and eigenvalue contrast was established. The major and minor cone axes are shown to be coincident with the second and third eigenvectors of the tensor, respectively, in the limit of many uniformly spaced diffusion-encoding directions. The deviation between the major cone axis and the second eigenvector was quantified for typical sets of diffusion-weighting (DW) directions. The elliptical CU provides more realistic error information for fiber-tracking algorithms and a quantitative basis for selecting DT imaging acquisition protocols.

Quantitative evaluation of acquisition parameters in three-dimensional imaging with multidetector computed tomography using human skull phantom.

This study evaluated the quantitative measurements of three-dimensional (3D) volume images using multidetector row computed tomography (MDCT) and one skull specimen. Twenty-one linear distances were measured five times each by vernier caliper. A dry human skull was imaged with MDCT for various acquisition parameters at slice thicknesses of 1.25, 2.50, 3.75, and 5.00 mm for the different acquisition modes of axial and spiral scan. The distance of each corresponding item displayed on 3D rendered images was measured seven times by an uninvolved observer using a 3D software tool. Data analysis was performed to determine if there were any statistically significant differences in acquisition parameters. No significant image differences were found among the scan modes for each slice thickness. For a given scan mode, acquisition slice thickness was the important factor for quantitative measurement of 3D rendered CT images.

Quantitative analysis of three-dimensional rendered imaging of the human skull acquired from multi-detector row computed tomography.

The purpose of this study was to evaluate the quantitative accuracy of three-dimensional (3D) rendered images acquired with multi-detector row computed tomography (MDCT) by means of distance measurements of a dry human skull for various slice thicknesses and acquisition modes. A radiologist directly measured the distance of line items on the skull surface to establish reference "gold standards." The skull specimen was scanned with a MDCT with various scanning parameters (slice thicknesses and acquisition modes). An observer measured the corresponding distances of the same items on 3D rendered images. The quantitative accuracy of distance measurements was statistically evaluated. There were no significant statistical differences (P value <.05) in accuracy of distance measurements among the scan modes. However, the results showed that acquisition slice thickness was the influential factor in determining the accuracy of the 3D rendered MDCT images. The quantitative analysis of distance measurement may be a useful tool evaluating the accuracy and defining optimal parameters of 3D rendered images.