Susceptibility-weighted imaging: current status and future directions

Abstract

Susceptibility-weighted imaging (SWI) is a method that uses the intrinsic nature of local magnetic fields to enhance image contrast in order to improve the visibility of various susceptibility sources and to facilitate diagnostic interpretation. It is also the precursor to the concept of the use of phase for quantitative susceptibility mapping (QSM). Nowadays, SWI has become a widely used clinical tool to image deoxyhemoglobin in veins, iron deposition in the brain, hemorrhages, microbleeds and calcification. In this article, we review the basics of SWI, including data acquisition, data reconstruction and post-processing. In particular, the source of cusp artifacts in phase images is investigated in detail and an improved multi-channel phase data combination algorithm is provided. In addition, we show a few clinical applications of SWI for the imaging of stroke, traumatic brain injury, carotid vessel wall, siderotic nodules in cirrhotic liver, prostate cancer, prostatic calcification, spinal cord injury and intervertebral disc degeneration. As the clinical applications of SWI continue to expand both in and outside the brain, the improvement of SWI in conjunction with QSM is an important future direction of this technology. Copyright © 2016 John Wiley & Sons, Ltd.

Keywords: cerebral microbleeds; multi-channel phase data combination; phase imaging; quantitative susceptibility mapping; stroke; susceptibility-weighted imaging.

Figure 1

Overview of data processing steps in SWI. 1: background phase removal. 2: generating the weighting masks using filtered phase images for conventional SWI. 3: quantitative susceptibility mapping (QSM). 4: generating the weighting masks using susceptibility maps for tSWI. 5: minimum intensity projection (mIP). 6. maximum intensity projection (MIP).

Figure 2

Background phase removal using forward modeling. a. Susceptibility map b. Unwrapped phase image at TE = 7.5ms. c. Resultant phase after subtracting the predicted phase induced by sinuses and bones. d. Homodyne high-pass pass filtering (k-space window size = 32×32) result of b. e. Homodyne high-pass filtering (k-space window size = 64×64) result of b. f. Homodyne high-pass filtering (k-space window size = 32×32) result of c. There are still remnant background phase artifacts even after applying a 64×64 high-pass filter to the original phase image (e). Removal of the predicted phase due to sinuses and bones helped in suppressing most of this unwanted background phase, together with a milder high-pass filter (arrows in d, e and f).

Figure 3

Conventional SWI vs. true SWI (tSWI). a. Minimum intensity projection (mIP) of conventional SWI. b. Single slice conventional SWI in sagittal view. c. High-pass filtered phase image. d. mIP of tSWI. e. Single slice tSWI in sagittal view. f. Susceptibility map generated from c using the geometry constrained iterative SWIM algorithm (65). The quality of conventional SWI is similar to that in tSWI for visualizing the veins in transverse view (a and d). The orientation dependent phase causes improper enhancement of the vein in sagittal view on conventional SWI (arrows in b and c). This orientation dependence is avoided in tSWI (arrows in e and f). Images in sagittal view (b, c, e, and f) are all at the same anatomical position, and were interpolated to isotropic resolution for better visualization.

Figure 4

The remnant flow induced phase and the visualization of the vessel wall of MCA on SWI and QSM. Data were collected using a fully flow-compensated double-echo sequence with TE1=7.5ms, TE2=17.5ms. a. Magnitude image at TE1. b. High-pass filtered phase image at TE1. c. Susceptibility map generated from b using a truncated k-space division algorithm with a k-space threshold 0.2 (64). d. Magnitude image at TE2. e. High-pass filtered phase image at TE2. f. SWI generated using e. On the filtered phase images, the vessel wall is better visualized at the shorter echo (b) than at the longer echo (e). The diamagnetic property of the vessel wall can be seen from both the filtered phase image and the susceptibility map (arrows). The remnant phase in the arteries indicates errors in flow compensation, mainly due to the presence of background field gradients.

Figure 5

Simultaneous MRA, SWI and QSM using the interleaved double-echo sequence. Data were collected on a Siemens 3T Verio system using a 32 channel head coil, with TE1/TE2/TR=6/19.2/24ms, FA=15° and voxel size 0.6×0.6×1.2mm³. a. TOF-MRA generated as the average of echo₁₁ and echo₂₁. b. Enhanced MRA by subtracting echo₂₂ from echo₁₂. c. Enhanced MRA by subtracting echo₂₂ from a (TOF-MRA). d. Enhanced MRA after venous structures were removed from c. e. Minimum intensity projection of SWI data generated from echo₁₂. f. Maximum intensity projection of susceptibility maps generated from echo₁₂, using the geometry constrained iterative SWIM algorithm (65). Small arteries are clearer on b and d than on a. Internal cerebral arteries, middle cerebral arteries and anterior cerebral arteries are better visualized on d than on b (arrows), due to the better flow compensation at the shorter echo. See the main text for the definition of different echoes.

Figure 6

Magnitude images (a to d), phase images (e to h) and the estimated coil sensitivity related phase in different views (i to l) for 4 different channels (columns). See the main text for details of the calculation of the coil sensitivity related phase. Images in sagittal view were scaled for better visualization. Multi-channel data combination without considering the variation in the sensitivity related phase components between different channels leads to singularities or cusp artifacts in the combined phase images.

Figure 7

Comparison of the effects of different multi-channel data combination algorithms on phase images (a to e), QSM (f to j) and SWI (k to o). a, f, k: simple magnitude weighted averaging. b, g, i: constant phase offset algorithm. c, h, m: double-echo phase combination. d, i, n: echo center correction (ECC) algorithm. e, j, o: channel-by-channel high-pass filtering. Data were collected using a double-echo sequence with TE1=7.38ms and TE2=17.6ms. Only the results correspond to TE2 are shown here.

Figure 8

Imaging cerebral venous oxygen saturation under different conditions using SWI and QSM. a and d: post acetazolamide administration. b and e: normal state. c and f: post caffeine administration. Here a to c are the minimum intensity projections of SWI, while d to f are the maximum intensity projections of the susceptibility maps generated using the geometry constrained iterative SWIM algorithm (65). The effective slice thickness is 20mm for all the images. Both the enhanced visibility of the veins on SWI from a to c and the increased susceptibilities on QSM from d to f reflect the increasing concentration of deoxyhemoglobin in the veins. The data for the acetazolamide and caffeine experiments were collected on different days, while the data for the normal state were collected before the caffeine administration during the caffeine experiment.

Figure 9

A 77-year-old male who suddenly had left limb weakness and paresthesia underwent an MR scan with PWI and SWI 3 hours after stroke. MTT (a) showed a large hypo-perfused region in the right lateral hippocampus and occipital lobe, while SWI (b) showed asymmetrically prominent cortical veins (APCV) in the corresponding region, as indicated by the red contour in b. Six days after intravenous rTPA treatment, with improved neurological symptoms, the patient underwent a second MR scan with PWI-MTT (c) and SWI (d), in which both MTT and SWI appeared normal.

Figure 10

Visualization and quantification of asymmetrically prominent cortical veins (APCV) in an ischemic stroke patient using SWI and QSM. a. DWI showed multiple high signal regions in the centrum semiovale and in the genu of the corpus callosum. b. Visualization of the APCV in the left hemisphere in the minimum intensity projection of SWI data. c. Maximum intensity projection of susceptibility maps showing cortical veins with increased susceptibility in the ischemic hemisphere, compared to those in the contralateral hemisphere. Susceptibility maps were generated using the geometry constrained iterative SWIM algorithm (65).

Figure 11

Visualization and quantification of the susceptibility of bilateral cortical veins in a 19-year-old female patient with right transverse sinus thrombosis. The right transverse sinus is less hypo-intense than normal on T2WI (a) and markedly hypo-intense and dilated on SWI (b), suggestive of early thrombosis. Bilateral cortical veins were dilated and increased levels of deoxyhemoglobin were indicated on the minimum intensity projection (mIP) of the SWI data (c) and the maximum intensity projection (MIP) of the QSM data (d). In the follow-up scan, both the T2WI (e) and the original magnitude image in the SWI data (f) showed hyper-intensity in the right transverse sinus, possibly due to evolving blood products in the thrombus (white arrows). Although a normal flow void did not return on T2WI, the increased oxygen saturation of the cortical veins may suggest early recanalization or collateral venous drainage in the brain, as indicated by both the mIP of SWI data (g) and the MIP of QSM data (h). For a to d, the original data were acquired at 1.5T (where the echo time of the SWI data was 40ms); while for e to h, the original data were acquired at 3T (where the echo time of the SWI data was 20ms). Susceptibility maps in d and h were generated using a truncated k-space division algorithm (64) with a k-space threshold 0.2. The effective slice thickness is 24mm in c, d g, and h.

Figure 12

Imaging cerebral microbleeds (CMB) using SWI and QSM. For this patient, there is a single CMB that is not visible in either T2WI (a) or FLAIR (d), but can be seen in the original magnitude (b) and filtered phase images (c) in the SWI data (white arrows). The CMB can be better visualized in the minimum intensity projection of SWI data (e) and the maximum intensity projection of susceptibility maps (f) (white arrows). The CMB appears as hypo-intense in b and e, while hyper-intense in c and f, indicating that it is paramagnetic. Note that the phase image shown in c was from a left-handed system. There is no connection between the CMB and vessels, as can be seen in both e and f. Susceptibility maps were generated using the geometry constrained iterative SWIM algorithm (65). The (effective) slice thickness is 2mm in a, 1.5mm in b and c, 0.5mm in d, 12mm in e and f.

Figure 13

Visualization and quantification of cortical veins on SWI (a) and QSM (b) in a 32-year-old male patient with diffuse axonal injury due to a traffic accident. The cortical veins near the cerebral microbleeds can be clearly seen in the frontal and parietal lobes (red arrows). Susceptibility maps were generated using the geometry constrained iterative SWIM algorithm (65).

Figure 14

Eccentric wall thickening (arrow) at the posterolateral aspect of the right common carotid artery on TOF-MRA (a). There is a dark spot on the magnitude image (b), which appears bright on both the filtered phase image (c) and the susceptibility map (d). This suggests that this is a tiny foci of intraplaque hemorrhage and may represent an example of vulnerable plaque. The original data for b, c and d were acquired using a multi-echo SWI sequence at 3T, although these images were generated using the data from the shortest echo with TE=5.18ms. Image c was generated using a homodyne high-pass filter with k-space window size 64×64, while d was generated using a truncated k-space division algorithm (64) with a k-space threshold 0.2.

Figure 15

Comparison of T2*WI (a) and SWI (b) for the detection of siderotic nodules (SN) in cirrhotic liver disease. The number of detected SN was 30 on T2*WI (a), and 139 on SWI (b). In the whole liver, the number of SN detected by SWI was nearly 5 times that detected by T2*WI (393 by T2*WI vs 1856 by SWI).

Figure 16

A 66-year-old man with prostate cancer in the peripheral zone of the prostate. Low signal on conventional T1WI (a) and T2WI (b) (arrows) indicates tumor hemorrhage. No hemorrhage is demonstrated on CT (c). The tumor hemorrhage was seen with SWI (d) and the filtered phase image (e) (arrows). The images in the second column came from another slice of the same patient. No prostatic calcification is demonstrated on conventional T1WI (f) and T2WI (g), but a dot-like high density on CT (h), low signal on SWI (i) and high signal on the filtered phase image (j) (arrows) indicates calcification. The filtered phase images (e and j) were from a right-handed system. Reproduced from ref. (145).

Figure 17

Imaging advanced intervertebral disc degeneration more than grade 4 by the Pfirrmann grading system in the lumbar spine using SWI and QSM. Intradiscal air in the L5-S1 intervertebral discs (arrows) is better visualized on the magnitude image (b), susceptibility map (c) and tSWI (d), than on T2WI (a). Susceptibility maps were generated using the geometry constrained iterative SWIM algorithm (65).