Investig Magn Reson Imaging.  2019 Mar;23(1):1-16. 10.13104/imri.2019.23.1.1.

Advanced Methods in Dynamic Contrast Enhanced Arterial Phase Imaging of the Liver

• Kim YC

• KMID: 2442228
• DOI: http://doi.org/10.13104/imri.2019.23.1.1

Abstract

Dynamic contrast enhanced (DCE) magnetic resonance (MR) imaging plays an important role in non-invasive detection and characterization of primary and metastatic lesions in the liver. Recently, efforts have been made to improve spatial and temporal resolution of DCE liver MRI for arterial phase imaging. Review of recent publications related to arterial phase imaging of the liver indicates that there exist primarily two approaches: breath-hold and free-breathing. For breath-hold imaging, acquiring multiple arterial phase images in a breath-hold is the preferred approach over conventional single-phase imaging. For free-breathing imaging, a combination of three-dimensional (3D) stack-of-stars golden-angle sampling and compressed sensing parallel imaging reconstruction is one of emerging techniques. Self-gating can be used to decrease respiratory motion artifact. This article introduces recent MRI technologies relevant to hepatic arterial phase imaging, including differential subsampling with Cartesian ordering (DISCO), golden-angle radial sparse parallel (GRASP), and X-D GRASP. This article also describes techniques related to dynamic 3D image reconstruction of the liver from golden-angle stack-of-stars data.

Keyword

Dynamic contrast enhanced MRI; Liver; Image reconstruction; Pulse sequence; Compressed sensing; GRASP

MeSH Terms

Artifacts
Hand Strength
Image Processing, Computer-Assisted
Liver*
Magnetic Resonance Imaging
Methods*

Figure

• 

  Fig. 1. DCE liver MRI scan protocols. (a) Schematic of a conventional DCE liver imaging protocol. All acquisition sequences have the same single-phase 3D fast gradient echo (GRE), which is referred to as eTHRIVE for Philips, VIBE for Siemens, and LAVA for GE, acquired within a breathhold (BH), typically lasting for 15 seconds. (b) Schematic of a modified protocol where a multiphase imaging method (green box) is substituted for the conventional single-phase acquisition of arterial phase. BH: breathhold; FB: free-breathing. (c) Schematic of a modified protocol where a multiphase FB imaging (green box) is used and the duration of FB imaging is extended to cover the portal venous phase. (d) Time versus MR signal curves from normal liver region of interest (ROI) and tumor ROI. The orange box indicates the acquisition time interval of single-phase BH imaging and the green box shows that of multiphase FB imaging. In single-phase BH imaging, start time of the acquisition is critical for differentiation of tumor enhancement from normal tissue.

• 

  Fig. 2. Schematic illustration of DISCO. (a) Sampling distribution. Section A is fully sampled in (ky, kz) while sections B, C, and D are undersampled in a pseudo-random manner. The union of samples from sections B, C, and D is fully sampled. (b) Temporal acquisition order of the k-space sections. Note that section A is acquired more frequently in time than sections B, C, and D.

• 

  Fig. 3. Schematic illustration of 3D GRASP. (a) 3D view of k-space sampling pattern. (b) 2D view in (kx, kz). (c) 2D view in (kx, ky). For a given angle spoke, it samples uniformly in kz axis until it fills out the kz space. The spoke angle is then incremented by golden angle α ≈ 180°/1.618 ≈ 111°, followed by filling out the kz space. This process is repeated until it reaches the prescribed number of radial spokes. (d) Continuous imaging sequence in 2D golden-angle radial sequence. The same principle can also be applied to 3D GRASP without loss of generality. The number in the green box indicates spoke order. (e, f) Sampling patterns after retrospective selections of temporal window by grouping (e) five consecutive spokes per frame and (f) three consecutive spokes per frame. For both cases (one with grouping of 5 spokes and the other with grouping of 3 spokes), patterns of angle spacing in radial spokes are similar in all frames. This is relevant to the fact that golden angle radial sampling guarantees temporal stability. Per frame basis, (e) is more densely sampled (less spatial aliasing) than (f). (e) has a lower frame rate than (f).

• 

  Fig. 4. Retrospective reconstructions from GRASP data. (a) Schematic of retrospective adjustment of a starting point (red dashed line) and temporal window (green and blue) from continuously acquired raw data in GRASP. (b) Retrospective reconstructions with choices of 40, 55, and 70 spokes. Results exhibit stable image reconstruction quality in all frames for the three cases.

• 

  Fig. 5. Illustration of data binning procedures in XD-GRASP. (a) Raw data samples at the center in (kx, ky) are extracted for each spoke t’ and are denoted by d1(kz, t’). (b) One-dimensional Fourier transform is performed along kz to transform data d1(kz, t’) to d2(z, t’) for each spoke t’. d2(z, t’) represents 1D projection signal projected to superior-inferior (S-I) direction. (c) Construction of a 2D image d3(z, t) by concatenating 1D projection data for all coils and all radial spokes. (d) A result of the first principal component after performing principal component analysis (PCA) of the 2D image d3(z, t). (e) A result of smooth version of (d) after taking a median filter in time. (f) Estimation of the envelope (red line) after a spline fitting to peak points in (e). (g) Flattened curve after division of (e) by (f). Final motion state assignment is indicated by different colors (state 1: red, state 2: blue, state 3: black, state 4: green). Contrast phases are differentiated by background colors in the plot.

• 

  Fig. 6. An example of reconstructed images using XD-GRASP. (a) Final reconstructed images of XD-GRASP. These images contain an additional respiratory motion-resolved dimension. (b) Comparison of GRASP and XD-GRASP for contrast phase 5. GRASP exhibits an image of averaged motion from all respiration states. XD-GRASP contains images, each of which is from a respiration state. Note that there are differences in image appearance between respiration states 1 and 4 (yellow and green arrows). Also note motion-averaged image appearance in the GRASP image (red and white arrows).

• 

  Fig. 7. Illustration of water fat separation from continuously acquired dual-echo 3D stack-of-stars golden-angle radial raw data. (a) Schematic of a radial dual-echo pulse sequence. (b) TE1 and TE2 images can be separately reconstructed using compressed sensing and parallel imaging. These complex-valued images are input to a 2-point Dixon water fat separation algorithm. The output is a set of water and fat images. Water-fat swap artifact is indicated by red arrows. (c) Final fat suppressed dynamic image frames are shown.

Reference

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